| As we may have thought, and may (still) think | | BIBAK | Full-Text | 1-2 | |
| Andrew Dillon | |||
| The promise of electronic documents is long lived yet curiously uninspiring
in execution. In this address I will revisit the promises and consider the
progress and problems faced over the last two decades in creating the
information spaces imagined by the field's founders. Keywords: e-books, human factors | |||
| Is this a good title? | | BIBAK | Full-Text | 3-12 | |
| Martin Klein; Jeffery Shipman; Michael L. Nelson | |||
| Missing web pages, URIs that return the 404 "Page Not Found" error or the
HTTP response code 200 but dereference unexpected content, are ubiquitous in
today's browsing experience. We use Internet search engines to relocate such
missing pages and provide means that help automate the rediscovery process. We
propose querying web pages' titles against search engines. We investigate the
retrieval performance of titles and compare them to lexical signatures which
are derived from the pages' content. Since titles naturally represent the
content of a document they intuitively change over time. We measure the edit
distance between current titles and titles of copies of the same pages obtained
from the Internet Archive and display their evolution. We further investigate
the correlation between title changes and content modifications of a web page
over time. Lastly we provide a predictive model for the quality of any given
web page title in terms of its discovery performance. Our results show that
titles return more than 60% URIs top ranked and further relevant content
returned in the top 10 results. We show that titles decay slowly but are far
more stable than the pages' content. We further distill stop titles than can
help identify insufficiently performing search engine queries. Keywords: digital preservation, web page discovery, web page titles | |||
| Parallel browsing behavior on the web | | BIBAK | Full-Text | 13-18 | |
| Jeff Huang; Ryen W. White | |||
| Parallel browsing describes a behavior where users visit Web pages in
multiple concurrent threads. Web browsers explicitly support this by providing
tabs. Although parallel browsing is more prevalent than linear browsing online,
little is known about how users perform this activity. We study the use of
parallel browsing through a log-based study of millions of Web users and
present findings on their behavior. We identify a power law distribution in
browser metrics comprising "outclicks" and tab switches, which signify the
degree of parallel browsing. We find that users switch tabs at least 57.4% of
the time, but user activity, measured in pageviews, is split among tabs rather
than increasing overall activity. Finally, analysis of a subset of the logs
focused on Web search shows that while the majority of users do not branch from
search engine result pages, the degree of branching is higher for
non-navigational queries. Our findings have design implications for Web sites
and browsers, search interfaces, and log analysis. Keywords: log mining, parallel browsing, tabs | |||
| A semiotic approach for the generation of themed photo narratives | | BIBAK | Full-Text | 19-28 | |
| Charlie Hargood; David E. Millard; Mark J. Weal | |||
| A wide variety of systems could be considered 'narrative systems', either
directly working towards generating rich narratives or, more frequently,
because they present or handle information in a narrative context. These
narratives, generated or otherwise handled, may contain themes; an essential
part of the subtext of narrative communicating important concepts outside the
capabilities of the literal meaning of the content and forming the thematic
cohesion that aids the flow of the presented narrative. However despite this
very little work has been undertaken to understand of take advantage of these
themes, particularly in narrative generation where the presence of well defined
themes may improve the richness of those generated narratives. In this paper we
evaluate the performance of a system utilising a thematic model in order to
generate simple narratives in the form of photo montages compared to a keyword
based system that does not. The experiment demonstrates that the system
utilising the thematic model is capable of successfully connoting themes within
these narratives. It also shows that the relevance of the resulting narratives
to the titles used to generate them is higher in the thematic system than those
generated by the other system. Keywords: folksonomies, narrative, narrative generation, semiotics, thematics | |||
| The impact of bookmarks and annotations on refinding information | | BIBAK | Full-Text | 29-34 | |
| Ricardo Kawase; George Papadakis; Eelco Herder; Wolfgang Nejdl | |||
| Refinding information has been interwoven with web activity since its early
beginning. Even though all common web browsers were equipped with a history
list and bookmarks early enough to facilitate this need, most users typically
use search engines to refind information. However, both bookmarks and search
based tools have significant limitations that impact their usability: the
former are known to be hard to manage over the course of time, whereas the
latter require the user to recall a specific combination of keywords or
context. Most importantly, though, both are particularly inappropriate in cases
where a piece of information is contained within an unstructured web page. In
this paper, we present in-context annotation as a more efficient alternative to
these methodologies. To verify this claim, we conducted a study in which we
compare the performance of experienced users in all three approaches while
revisiting specific pieces of information in the web after a long period of
time. The outcomes suggest that in-context annotation clearly outperforms both
traditional strategies. Keywords: evaluation, information refinding, user study, web annotation | |||
| Automatic construction of travel itineraries using social breadcrumbs | | BIBAK | Full-Text | 35-44 | |
| Munmun De Choudhury; Moran Feldman; Sihem Amer-Yahia; Nadav Golbandi; Ronny Lempel; Cong Yu | |||
| Vacation planning is one of the frequent -- but nonetheless laborious --
tasks that people engage themselves with online; requiring skilled interaction
with a multitude of resources. This paper constructs intra-city travel
itineraries automatically by tapping a latent source reflecting geo-temporal
breadcrumbs left by millions of tourists. For example, the popular rich media
sharing site, Flickr, allows photos to be stamped by the time of when they were
taken and be mapped to Points Of Interests (POIs) by geographical (i.e.
latitude-longitude) and semantic (e.g., tags) metadata.
Leveraging this information, we construct itineraries following a two-step approach. Given a city, we first extract photo streams of individual users. Each photo stream provides estimates on where the user was, how long he stayed at each place, and what was the transit time between places. In the second step, we aggregate all user photo streams into a POI graph. Itineraries are then automatically constructed from the graph based on the popularity of the POIs and subject to the user's time and destination constraints. We evaluate our approach by constructing itineraries for several major cities and comparing them, through a "crowd-sourcing" marketplace (Amazon Mechanical Turk), against itineraries constructed from popular bus tours that are professionally generated. Our extensive survey-based user studies over about 450 workers on AMT indicate that high quality itineraries can be automatically constructed from Flickr data. Keywords: flickr, geo-tags, mechanical turk, orienteering problem, social media,
travel itinerary | |||
| Speak the same language with your friends: augmenting tag recommenders with social relations | | BIBAK | Full-Text | 45-50 | |
| Kaipeng Liu; Binxing Fang; Weizhe Zhang | |||
| Many existing tag recommendation approaches ignore the social relations
between users. In this paper, we investigate the role of such additional
information for the task of personalized tag recommendation. We inject the
social relations between users and the content similarities between resources,
along with the social annotations made by collaborative users, into a graph
representation. To fully explore the structure of this graph, we exploit the
methodology of random-walk computation of similarities between all the objects.
We develop a personalized collaborative filtering algorithm that combines both
the collaborative information and the personalized tag preferences. Experiments
on Delicious data demonstrate the effectiveness of the proposed methods. Keywords: personalization, social tagging, tag recommendation | |||
| Connecting users and items with weighted tags for personalized item recommendations | | BIBAK | Full-Text | 51-60 | |
| Huizhi Liang; Yue Xu; Yuefeng Li; Richi Nayak; Xiaohui Tao | |||
| Tags are an important information source in Web 2.0. They can be used to
describe users' topic preferences as well as the content of items to make
personalized recommendations. However, since tags are arbitrary words given by
users, they contain a lot of noise such as tag synonyms, semantic ambiguities
and personal tags. Such noise brings difficulties to improve the accuracy of
item recommendations. To eliminate the noise of tags, in this paper we propose
to use the multiple relationships among users, items and tags to find the
semantic meaning of each tag for each user individually. With the proposed
approach, the relevant tags of each item and the tag preferences of each user
are determined. In addition, the user and item-based collaborative filtering
combined with the content filtering approach are explored. The effectiveness of
the proposed approaches is demonstrated in the experiments conducted on real
world datasets collected from Amazon.com and citeULike website. Keywords: personalization, recommender systems, tags, web 2.0 | |||
| Topic-based personalized recommendation for collaborative tagging system | | BIBAK | Full-Text | 61-66 | |
| Yanhui Guo; James B. D. Joshi | |||
| Collaborative tagging has become a very popular way to share, annotate, and
discover online resources in Web 2.0. Yet as the number of resources in
Collaborative tagging system grows over time, sifting through the large amounts
of resources and finding the right resources to recommend to the right user is
becoming a challenging problem. In this paper, we investigate a probabilistic
generative model for collaborative tagging, explore the implicit semantic
connections in the sparse and noisy information space of heterogeneous users
and unsupervised tagging. First, a modified Latent Dirichlet Allocation (LDA)
model is used to cluster the tags and users simultaneously. The generalization
of resource description and user could alleviate the tag noise and data
sparseness of recommendation effectively. And then, considering that
topic-based recommendation only takes the users' global interest into
consideration without the capability of distinguishing users' interest in
detail, we combine the global interests with the individual interest and
community interest. Experimental results demonstrate the topic-based
personalized recommendation method, which integrate both the commonality factor
among users and the specialties of individuals, could alleviate data sparsity
and provide a more flexible and effective recommendation than previous methods. Keywords: collaborative tagging, latent topic models, personalization, recommendation | |||
| Providing resilient XPaths for external adaptation engines | | BIBAK | Full-Text | 67-76 | |
| Iñaki Paz; Oscar Díaz | |||
| Approaches to Web application adaptation can be classified based on whether
the application is aware of the adaptation or not. In the latter case,
adaptation is referred to as external. External adaptation requires the use of
addressing patterns that locate the target portion/data on the application
pages to be adapted. Unfortunately, changes on the application normally also
require updates to the addressing patterns. This raises pattern robustness as a
main concern. This papers focuses on the (semi) automatic generation of
change-resilience XPath patterns. Two different categories of changes are
addressed, i.e. in space (e.g., different personalizations of a page) and in
time (e.g., site upgrades), by exploiting two different techniques: induction
and simulated annealing. These techniques permit to obtain XPath patterns
"resilient-enough" to a "controlled set of page designs". SiSy, a tool that
assists the user in obtaining resilient XPath expressions, was born out of this
approach. The approach is tested for two websites (www.yahoo.com and
www.elmundo.es), identifying 23 updates to which XPath expressions were
resilient to 62% of the undertaken changes. Keywords: change resilience, evolution, external adaptation, xpath | |||
| The influence of adaptation on hypertext structures and navigation | | BIBAK | Full-Text | 77-82 | |
| Vinicius Faria Culmant Ramos; Paul M. E. de Bra | |||
| In adaptive hypertexts the user is guided in two ways: through the existence
of link and through link annotation or hiding. Link structures have been
investigated, starting with Botafogo et al, and the effect of link annotation
has been studied, for instance by Brusilovsky et al. This paper studies the
combined effect of link structure and annotation/hidin on the navigation
patterns of users. It defines empirical hubs and studies their correlation with
hubs as defined by Kleinberg without considering adaptation. The data for the
analysis have been extracted from the logs of the course "Hypermedia Structures
and Systems," an online adaptive course offered at the Eindhoven University of
Technology. Keywords: adaptive hypermedia, evaluation, navigation, structural analysis | |||
| The next generation authoring adaptive hypermedia: using and evaluating the MOT3.0 and PEAL tools | | BIBAK | Full-Text | 83-92 | |
| Jonathan G. K. Foss; Alexandra I. Cristea | |||
| Adaptive hypermedia allows for customization to the needs of the user. The
authoring process however is not trivial, and is often the main hurdle to
overcome in order to bring this useful paradigm to a greater number of users.
In this paper, we discuss the major problems occurring in authoring of adaptive
hypermedia, and propose a set of generic authoring imperatives, to be consulted
by any system implementing creation tools for customization of content. Based
on these imperatives, in this paper we extensively illustrate and discuss
recent extensions and improvements we have implemented in the My Online Teacher
(MOT) adaptation authoring tool set, including the MOT3.0 content authoring and
labeling tool and the PEAL adaptation strategy author. Furthermore, we
evaluate, compare and discuss two long term uses of the MOT tool set, first in
2008 and the second in 2009. Keywords: adaptive hypermedia, authoring tools, lag, laos, mot | |||
| Provenance meets adaptive hypermedia | | BIBAK | Full-Text | 93-98 | |
| Evgeny Knutov; Paul De Bra; Mykola Pechenizkiy | |||
| In this paper we consider provenance modelling in Adaptive Hypermedia
Systems (AHS). We revisit adaptation and data provenance questions and bring up
new and complementary aspects of adaptation and provenance, showing similar and
supplementing characteristics. We also scrutinize the provenance importance and
issues in Adaptive Hypermedia (AH). The aim of this paper is to extend the
conventional AH classification questions with the notion of data lineage which
essentially plays an important role in adaptation. Keywords: adaptation questions, adaptive hypermedia, provenance, w7 provenance model | |||
| Assisting two-way mapping generation in hypermedia workspace | | BIBAK | Full-Text | 99-108 | |
| Haowei Hsieh; Katherine Pauls; Amber Jansen; Gautam Nimmagadda; Frank Shipman | |||
| This paper reports our study of a two-way mapping generation tool called
Mapping Assistant, as an extension to the Spatial Hypermedia system VITE.
Mapping Assistant has been designed to overcome the problem arising due to the
difficulty of users in generating an initial two-way mapping for VITE. We have
developed VITE to allow users to interact with information in a semi-formal
workspace. Creating two-way mapping profiles is a vital step for projecting
structured information into a spatial hypermedia system. A previous study of
VITE indicated that users spent much of their time developing an initial
mapping before working on the information task. We designed the Mapping
Assistant to assist users by generating a quick initial mapping from the data
entered by the user and reduce the cognitive and mental load on the user. This
research studies users' impression of the Mapping Assistant. The results
indicate that the users liked the Mapping Assistant and found it useful, but
comments from users also reveal possible directions for further improvement of
the tool and its design. Keywords: editable visualizations, information visualization, information workspace,
spatial hypertext, two-way mappings | |||
| Analysis of graphs for digital preservation suitability | | BIBAK | Full-Text | 109-118 | |
| Charles L. Cartledge; Michael L. Nelson | |||
| We investigate the use of autonomically created small-world graphs as a
framework for the long term storage of digital objects on the Web in a
potentially hostile environment. We attack the classic Erdos -- Renyi random,
Barabási and Albert power law, Watts -- Strogatz small world and our
Unsupervise. Small World (USW) graphs using different attacker strategies and
report their respective robustness. Using different attacker profiles, we
construct a game where the attacker is allowed to use a strategy of his choice
to remove a percentage of each graph's elements. The graph is then allowed to
repair some portion of its self. We report on the number of alternating attack
and repair turns until either the graph is disconnected, or the game exceeds
the number of permitted turns. Based on our analysis, an attack strategy that
focuses on removing the vertices with the highest betweenness value is most
advantageous to the attacker. Power law graphs can become disconnected with the
removal of a single edge; random graphs with the removal of as few as 1% of
their vertices, small-world graphs with the removal of 14% vertices, and USW
with the removal of 17% vertices. Watts -- Strogatz small-world graphs are more
robust and resilient than random or power law graphs. USW graphs are more
robust and resilient than small world graphs. A graph of USW connected WOs
filled with date could outlive the individuals and institutions that created
the data in an environment where WOs are lost due to random failures or
directed attacks. Keywords: resilience, robustness, small world | |||
| iMapping: a zooming user interface approach for personal and semantic knowledge management | | BIBAK | Full-Text | 119-128 | |
| Heiko Haller; Andreas Abecker | |||
| We present iMapping, a zooming based approach for visually organizing
information objects. It was developed on top of semantic desktop technologies
and especially targets the support of personal knowledge management. iMapping
has been designed to combine the advantages of spatial hypertext and other
proven visual mapping approaches like mind-mapping and concept mapping, which
are incompatible in their original form. We describe the design and
prototypical implementation of iMapping -- which is fundamentally based on deep
zooming and nesting. iMapping bridges the gap between unstructured content like
informal text notes and semantic models by allowing annotations with the whole
range from vague associations to formal relations. First experimental
evaluation of the iMapping user-interface approach indicates favorable user
experience and functionality, compared with state-of-the-art Mind-Mapping
software. Keywords: human-computer interaction, interaction design, personal knowledge
management, semantic desktop, spatial hypertext, visual knowledge mapping | |||
| Modularity for heterogeneous networks | | BIBAK | Full-Text | 129-134 | |
| Tsuyoshi Murata | |||
| Online social media such as delicious and digg are represented as tripartite
networks whose vertices are users, tags, and resources. Detecting communities
from such tripartite networks is practically important. Modularity is often
used as the criteria for evaluating the goodness of network divisions into
communities. Although Newman-Girvan modularity is popular for unipartite
networks, it is not suitable for n-partite networks. For bipartite networks,
Barber, Guimera, Murata and Suzuki define bipartite modularities. For
tripartite networks, Neubauer defines tripartite modularity which extends
Murata's bipartite modularity. However, Neubauer's tripartite modularity still
uses projections and it will lose information that original tripartite networks
have. This paper proposes new tripartite modularity for tripartite networks
that do not use projections. Experimental results show that better community
structures can be detected by optimizing our tripartite modularity. Keywords: complex network | |||
| Link prediction applied to an open large-scale online social network | | BIBAK | Full-Text | 135-140 | |
| Dan Corlette; Frank M., III Shipman | |||
| In this paper, we describe experiments examining the practicality of
applying link prediction to an open large-scale online social network. We rely
on metrics that are strictly topological, making use of one previously
identified metric and one of our own. We directly address the open nature of
the network through a study of the linking dynamics over time between users and
the effect the openness of the network (i.e. users entering/leaving the
network) has on our ability to predict new friendship links. We follow users
from the time they enter the network to 10 months after joining and examine the
effect of applying link prediction at different points. Analysis shows that
prediction results are best shortly after users have entered the network and
that the precision and recall of link prediction results diminish the longer
users have been members of the network. To the best of our knowledge, our
analysis is the most comprehensive in terms of analyzing link prediction in an
open large-scale online social network. Keywords: link prediction, network dynamics, social networks | |||
| Community-based ranking of the social web | | BIBAK | Full-Text | 141-150 | |
| Said Kashoob; James Caverlee; Krishna Kamath | |||
| The rise of social interactions on the Web requires developing new methods
of information organization and discovery. To that end, we propose a generative
community-based probabilistic tagging model that can automatically uncover
communities of users and their associated tags. We experimentally validate the
quality of the discovered communities over the social bookmarking system
Delicious. In comparison to an alternative generative model (Latent Dirichlet
Allocation (LDA), we find that the proposed community-based model improves the
empirical likelihood of held-out test data and discovers more coherent
interest-based communities. Based on the community-based probabilistic tagging
model, we develop a novel community-based ranking model for effective
community-based exploration of socially-tagged Web resources. We compare
community-based ranking to three state-of-the-art retrieval models: (i) BM25;
(ii) Cluster-based retrieval using K-means clustering; and (iii) LDA-based
retrieval. We find that the proposed ranking model results in a significant
improvement over these alternatives (from 7% to 22%) in the quality of
retrieved pages. Keywords: community, ranking, social, tagging | |||
| Social networks and interest similarity: the case of CiteULike | | BIBAK | Full-Text | 151-156 | |
| Danielle H. Lee; Peter Brusilovsky | |||
| In collaborative filtering recommender systems, there is little room for
users to get involved in the choice of their peer group. It leaves users
defenseless against various spamming or ''shilling'' attacks. Other social
Web-based systems, however, allow users to self-select peers and build a social
network. We argue that users' self-defined social networks could be valuable to
increase the quality of recommendation in CF systems. To prove the feasibility
of this idea we examined how similar are interests of users connected by
self-defined relationships in a collaborative tagging systems Citeulike.
Interest similarity was measured by similarity of items and meta-data they
share and tags they use. Our study shows that users connected by social
networks exhibit significantly higher similarity on all explored levels (items,
meta-data, and tags) than non-connected users. This similarity is the highest
for directly connected users and decreases with the increase of distance
between users. Among other interesting properties of information sharing is the
finding that between-user similarity in social connections on the level of
metadata and tags is much larger than similarity on the level of items.
Overall, our findings support the feasibility of social network based
recommender systems and offer some good hints to the prospective authors of
these systems. Keywords: citeulike, information sharing, social networks | |||
| Of categorizers and describers: an evaluation of quantitative measures for tagging motivation | | BIBAK | Full-Text | 157-166 | |
| Christian Körner; Roman Kern; Hans-Peter Grahsl; Markus Strohmaier | |||
| While recent research has advanced our understanding about the structure and
dynamics of social tagging systems, we know little about (i) the underlying
motivations for tagging (why users tag), and (ii) how they influence the
properties of resulting tags and folksonomies. In this paper, we focus on
problem (i) based on a distinction between two types of user motivations that
we have identified in earlier work: Categorizers vs. Describers. To that end,
we systematically define and evaluate a number of measures designed to
discriminate between describers, i.e. users who use tags for describing
resources as opposed to categorizers, i.e. users who use tags for categorizing
resources. Subsequently, we present empirical findings from qualitative and
quantitative evaluations of the measures on real world tagging behavior. In
addition, we conducted a recommender evaluation in which we study the
effectiveness of each of the presented measures and found the measure based on
the tag content to be the most accurate in predicting the user behavior closely
followed by a content independent measure. The overall contribution of this
paper is the presentation of empirical evidence that tagging motivation can be
approximated with simple statistical measures. Our research is relevant for (a)
designers of tagging systems aiming to better understand the motivations of
their users and (b) researchers interested in studying the effects of users'
tagging motivation on the properties of resulting tags and emergent structures
in social tagging systems. Keywords: measures, social software, tagging, user motivation | |||
| Of kings, traffic signs and flowers: exploring navigation of tagged documents | | BIBAK | Full-Text | 167-172 | |
| Jacek Gwizdka | |||
| Many popular Web 2.0 sites support navigation of tagged web resources. The
tag-based navigation has been described as a lightweight reorientation of view
on tags and the associated web resources. But is this navigation really
lightweight? This paper briefly presents an interface created to support
navigation of tagged documents. The paper then describes a study that explored
users' understanding of the tag-based navigation process and the underlying
information space. The results point to difficulties in promoting correct
understanding of complex relationships between documents and tags and to the
need for creating interfaces that support navigation continuity. Keywords: information space metaphors, pivot browsing, tag clouds | |||
| Conversational tagging in twitter | | BIBAK | Full-Text | 173-178 | |
| Jeff Huang; Katherine M. Thornton; Efthimis N. Efthimiadis | |||
| Users on Twitter, a microblogging service, started the phenomenon of adding
tags to their messages sometime around February 2008. These tags are distinct
from those in other Web 2.0 systems because users are less likely to index
messages for later retrieval. We compare tagging patterns in Twitter with those
in Delicious to show that tagging behavior in Twitter is different because of
its conversational, rather than organizational nature. We use a mixed method of
statistical analysis and an interpretive approach to study the phenomenon. We
find that tagging in Twitter is more about filtering and directing content so
that it appears in certain streams. The most illustrative example of how
tagging in Twitter differs is the phenomenon of the Twitter micro-meme:
emergent topics for which a tag is created, used widely for a few days, then
disappears. We describe the micro-meme phenomenon and discuss the importance of
this new tagging practice for the larger real-time search context. Keywords: memes, tagging, trends, twitter | |||
| The impact of resource title on tags in collaborative tagging systems | | BIBAK | Full-Text | 179-188 | |
| Marek Lipczak; Evangelos Milios | |||
| Collaborative tagging systems are popular tools for organization, sharing
and retrieval of web resources. Their success is due to their freedom and
simplicity of use. To post a resource, the user should only define a set of
tags that would position the resource in the system's data structure --
folksonomy. This data structure can serve as a rich source of information about
relations between tags and concepts they represent. To make use of information
collaboratively added to folksonomies, we need to understand how users make
tagging decisions. Three factors that are believed to influence user tagging
decisions are: the tags used by other users, the organization of user's
personal repository and the knowledge model shared between users. In our work
we examine the role of another potential factor -- resource title. Despite all
the advantages of tags, tagging is a tedious process. To minimize the effort,
users are likely to tag with keywords that are easily available. We show that
resource title, as a source of useful tags, is easy to access and comprehend.
Given a choice of two tags with the same meaning, users are likely to be
influenced by their presence in the title. However, a factor that seems to have
stronger impact on users' tagging decisions is maintaining the consistency of
the personal profile of tags. The results of our study reveal a new, less
idealistic picture of collaborative tagging systems, in which the collaborative
aspect seems to be less important than personal gains and convenience. Keywords: collaborative tagging, folksonomies, modelling | |||
| A narrative-based alternative to tagging | | BIBAK | Full-Text | 189-194 | |
| Nuno Tomás; Tiago Guerreiro; Joaquim A. Jorge; Daniel Gonçalves | |||
| The enormous dissemination of multimedia information over the past few years
has led to mechanisms to support its organization, cataloging and search
through descriptions or keywords. A popular way of associating such
descriptions to content is tagging as can be found in popular sites such as
Flickr (for images) or Delicious (bookmarks). This method allows users to
associate tags to media, richly describing its content and may help in its
retrieval at a later time. However, the process is mostly unstructured, leading
to several problems. Nothing guarantees that the tags used are the most
appropriate or the same tags are used in similar situations, making retrieval
difficult..
Our approach relies on narrative-based interfaces which use stories as an organizing principle for tagging media. Given that humans have used stories to communicate since the dawn of time, narrative is a natural form of interaction. By inter-relating bits of information into a coherent whole, stories convey data in a rich, structured way. A study carried out with 40 users over a period of three months shows that users convey almost six times more information when using narratives to describe their media than what is typical of traditional methods. Furthermore, our pilot study saw narratives increasing tag reuse to 94%. Finally, other problems found in tagging such as synonyms and polysemy were notably absent from story-generated tags. Keywords: digital media, narrative-based interfaces, tagging | |||
| UrbanWeb: a platform for mobile context-aware social computing | | BIBAK | Full-Text | 195-200 | |
| Frank Allan Hansen; Kaj Grønbæk | |||
| UrbanWeb is a novel Web-based context-aware hypermedia platform. It provides
essential mechanisms for mobile social computing applications: the framework
implements context as an extension to Web 2.0 tagging and provides developers
with an easy to use platform for mobile context-aware applications. Services
can be statically or dynamically defined in the user's context, data can be
precached for data intensive mobile applications, and shared state supports
synchronization between running applications such as games. The paper discusses
how UrbanWeb acquires cues about the user's context from sensors in mobile
phones, ranging from GPS data, to 2D barcodes, and manual entry of context
information, as well as how to utilize this context in applications. The
experiences show that the UrbanWeb platform efficiently supports a rich variety
of urban computing applications in different scales of user populations. Keywords: context-awareness, geo-spatial hypermedia, mobile web, multimedia blogging,
physical hypermedia, social computing, urban computing | |||
| Hyperorders and transclusion: understanding dimensional hypertext | | BIBAK | Full-Text | 201-210 | |
| James O. Goulding; Timothy J. Brailsford; Helen L. Ashman | |||
| ZigZag is a unique hyperstructural paradigm designed by the hypertext
pioneer Ted Nelson. It has piqued a lot of interest in the hypertext community
in recent years because of its aim of revolutionizing electronic access to
information and knowledge bases. In ZigZag information is stored in cells that
are arranged into lists organized along unlimited numbers of intersecting sets
of associations called dimensions. To this infrastructure a mechanism of
transclusion is added, allowing the data stored in cells to span, and hence be
utilized, in different contexts. Proponents of ZigZag claim that it is a
flexible and universal structure for information representation, and yet the
system has not been widely adopted and has been implemented even more rarely.
In this paper we address the question of whether there are intrinsic
theoretical reasons as to why this is the case.
While the basic features and specifications of ZigZag are well known, we delve in to the less understood area of its theoretical underpinnings to tackle this question. By modeling ZigZag within the framework of set theory we reveal a new class of hyperstructure that contains no referencable link objects whatsoever, instead grouping non-referencable binary associations into disjunct but parallel sets of common semantics (dimensions). We go on to further specialize these "dimensional models" into sets of finite partial functions, which are closed over a single domain, isolating the new class of hyperstructures we are calling hyperorders. This analysis not only sheds light on the benefits and limitations of the ZigZag hypermedia system, but also provides a framework to describe and understand a wider family of possible hyperstructure models of which it is an early example. Characteristics of Zigzag's transclusion mechanisms are also investigated, highlighting a previously unrecognized distinction, and potential irrevocable conflict, between two distinct uses of content reuse: instance and identity transclusion. Keywords: hypermedia structure, hyperorder, hyperstructure, set theory, transclusion,
zigzag | |||
| Evaluating hypertext: the quantitative-qualitative quandary | | BIBAK | Full-Text | 211-212 | |
| Mark Chignell; Peter Brusilovsky; Steve Szigeti; Elaine Toms | |||
| This panel will examine issues regarding the evaluation of hypertext
research. The panelists will begin by contrasting four different viewpoints on
the role of evaluation in hypertext research. The discussion will then consider
questions relating the what evaluation methods should be used and when. Keywords: evaluation, hypertext research | |||
| Design and evaluation of a hypervideo environment to support veterinary surgery learning | | BIBAK | Full-Text | 213-222 | |
| Claudio A. B. Tiellet; André Grahl Pereira; Eliseo Berni Reategui; José Valdeni Lima; Teresa Chambel | |||
| In the search of alternative ways to learning veterinary surgery with live
animals, hypervideo was considered a promising candidate as a learning tool.
Video can enhance the realism and authenticity of a learning environment. By
adding structure and interactivity to video, hypervideo allows to navigate
video and to explore other related media to complement it. Hypervideo might
then support the creation of a rich and realistic learning environment, through
the interactive access, construction and communication of knowledge on
veterinary surgery. In this paper, we present the design and evaluation of
Hvet, a hypervideo environment to support learning of veterinary surgery.
Design was based on cognitive and media theories, and evaluation was based on
the use of Hvet by veterinary students, in order to test its efficacy in
substitution of learning and training with live animals. Results support the
hypothesis, showing the potential of hypervideo as a valuable and effective
tool to support learning of surgery techniques and revealing the most
appreciated design options. Keywords: design, evaluation, high education, hypervideo, surgery, veterinary, video | |||
| The value of adaptive link annotation in e-learning: a study of a portal-based approach | | BIBAK | Full-Text | 223-228 | |
| I-Han Hsiao; Peter Brusilovsky; Michael Yudelson; Alvaro Ortigosa | |||
| Adaptive link annotation is one of the most popular adaptive educational
hypermedia techniques. It has been widely studied and demonstrated its ability
to help students to acquire knowledge faster, improve learning outcomes, reduce
navigation overhead, increase motivation, and encourage the beneficial
non-sequential navigation. However, almost all studies of adaptive link
annotation have been performed in the context of dedicated adaptive educational
hypermedia systems. The role of this technique in the context of widely popular
learning portals has not yet been demonstrated. In this paper, we attempt to
fill this gap by investigating the value of adaptive navigation support
embedded into the learning portal. We compare the effect of portal-based
adaptive navigation support to both the effect of the adaptive navigation
support in adaptive educational hypermedia systems and to non-adaptive learning
portals. Keywords: adaptive hypermedia, e-learning, motivation, navigation support, open corpus
adaptive hypermedia., portal self-assessment | |||
| Agents, bookmarks and clicks: a topical model of web navigation | | BIBAK | Full-Text | 229-234 | |
| Mark R. Meiss; Bruno Gonçalves; José J. Ramasco; Alessandro Flammini; Filippo Menczer | |||
| Analysis has shown that the standard Markovian model of Web navigation is a
poor predictor of actual Web traffic. Using empirical data, we characterize
several properties of Web traffic that cannot be reproduced with Markovian
models but can be explained by an agent-based model that adds several realistic
browsing behaviors. First, agents maintain bookmark lists used as teleportation
targets. Second, agents can retreat along visited links, a branching mechanism
that can reproduce behavior such the back button and tabbed browsing. Finally,
agents are sustained by visiting pages of topical interest, with adjacent pages
being related. This modulates the production of new sessions, recreating
heterogeneous session lengths. The resulting model reproduces individual
behaviors from empirical data, reconciling the narrowly focused browsing
patterns of individual users with the extreme heterogeneity of aggregate
traffic measurements, and leading the way to more sophisticated, realistic, and
effective ranking and crawling algorithms. Keywords: agent-based model, back button, bookmarks, bookrank, browsing, clicks,
entropy, interest, navigation, pagerank, sessions, topicality, traffic, web
links | |||
| Criticism | | BIBAK | Full-Text | 235-244 | |
| Mark Bernstein | |||
| Our methods for accumulating and testing evidence of a hypertext's successes
and shortcomings are numerous but poorly understood. This paper surveys the
most influential approaches to evaluating hypertexts and considers their impact
on crafting a new literary economy. Keywords: criticism, economics, fiction, hypertext narrative, publishing | |||
| Capturing implicit user influence in online social sharing | | BIBAK | Full-Text | 245-254 | |
| Ching-man Au Yeung; Tomoharu Iwata | |||
| Online social sharing sites are becoming very popular nowadays among Web
users, who use these sites to share their favourite items and to discover
interesting and useful items from other users. While an explicit social network
is not necessarily present in these sites, it is still possible that users
influence one another in the process of item adoption through various implicit
mechanisms. In this paper, we study how we can capture the implicit influences
among the users in a social sharing site. We propose a probabilistic model for
user adoption behaviour, where we assume that when user adopts an item, he
would pick a user and choose from the set of items that this user has adopted.
By using the model, we estimate the probability that one user influences
another user in the course of item adoption, based on the temporal adoption
pattern of the users. We carry out empirical studies of the model on Delicious,
a popular social bookmarking site. Experiments show that our model can be used
to predict item adoption more accurately than using collaborative filtering
techniques. We find that the strength of implicit influence various across
different topics. We also show that our method is able to identify the
influential users who are more likely to possess items interested by other
users. Our model can be used to study the dynamics in a social sharing site and
to complement collaborative filtering in recommendation systems. Keywords: collaborative tagging, social influence, social sharing | |||
| Interpretation and visualization of user history in a spatial hypertext system | | BIBAK | Full-Text | 255-264 | |
| DoHyoung Kim; Frank M. Shipman | |||
| We describe a new history mechanism based on experiences with the use of
recorded interaction history in the Visual Knowledge Builder (VKB). Problems
with the use of history in prior systems include difficulty in locating
activity of interest in large tasks, the problem of history records being at a
system activity level rather than a human activity level, and difficulty in
supporting navigation and comprehension in the branching histories used to
represent alternative directions. To support comprehension of the history, we
describe automatic history clustering to group low-level system events into a
more human-level representation of activity and the extraction of information
for summarizing these groups of events. To further support navigation and
comprehension of history, the mechanism includes multiple visualization
techniques to match diverse uses of history. The new history mechanism is
integrated into VKB 3. Keywords: asynchronous collaboration, awareness, branching history, history, spatial
hypertext, user activity records, visualization, vkb | |||
| Visit me, click me, be my friend: an analysis of evidence networks of user relationships in BibSonomy | | BIBAK | Full-Text | 265-270 | |
| Folke Mitzlaff; Dominik Benz; Gerd Stumme; Andreas Hotho | |||
| The ongoing spread of online social networking and sharing sites has
reshaped the way how people interact with each other. Analyzing the relatedness
of different users within the resulting large populations of these systems
plays an important role for tasks like user recommendation or community
detection. Algorithms in these fields typically face the problem that explicit
user relationships (like friend lists) are often very sparse. Surprisingly,
implicit evidences (like click logs) of user relations have hardly been
considered to this end.
Based on our long-time experience with running BibSonomy [4], we identify in this paper different evidence networks of user relationships in our system. We broadly classify each network based on whether the links are explicitly established by the users (e.g., friendship or group membership) or accrue implicitly in the running system (e.g., when user u copies an entry of user v). We systematically analyze structural properties of these networks and whether topological closeness (in terms of the length of shortest paths) coincides with semantic similarity between users. Our results exhibit different characteristics and. provide preparatory work for the inclusion of new (and less sparse) information into the process of optimizing community detection or user recommendation algorithms. Keywords: community detection, folksonomies, social networks, user recommendation | |||
| SnoopyDB: narrowing the gap between structured and unstructured information using recommendations | | BIBAK | Full-Text | 271-272 | |
| Wolfgang Gassler; Eva Zangerle; Michael Tschuggnall; Günther Specht | |||
| Knowledge is structured -- until it is stored to a wiki-like information
system. In this paper we present the multi-user system SnoopyDB, which
preserves the structure of knowledge without restricting the type or schema of
inserted information. A self-learning schema system and recommendation engine
support the user during the process of inserting information. These dynamically
calculated recommendations develop an implicit schema, which is used by the
majority of stored information. Further recommendation measures enhance the
content both semantically and syntactically and motivate the user to insert
more information than he intended to. Keywords: human interaction, ranking, rdf, recommendations, semantic web,
semistructured data | |||
| Citation based plagiarism detection: a new approach to identify plagiarized work language independently | | BIBAK | Full-Text | 273-274 | |
| Bela Gipp; Jöran Beel | |||
| This paper describes a new approach towards detecting plagiarism and
scientific documents that have been read but not cited. In contrast to existing
approaches, which analyze documents' words but ignore their citations, this
approach is based on citation analysis and allows duplicate and plagiarism
detection even if a document has been paraphrased or translated, since the
relative position of citations remains similar. Although this approach allows
in many cases the detection of plagiarized work that could not be detected
automatically with the traditional approaches, it should be considered as an
extension rather than a substitute. Whereas the known text analysis methods can
detect copied or, to a certain degree, modified passages, the proposed approach
requires longer passages with at least two citations in order to create a
digital fingerprint. Keywords: citation analysis, citation order analysis, duplicate detection, language
independent, plagiarism detection | |||
| Balancing content contextualization and accessibility in engineering assessment | | BIBAK | Full-Text | 275-276 | |
| Chirag Variawa; Susan McCahan | |||
| It has been suggested that the teaching of engineering content should
include integration across subject matter and contextualization of the
material. However, contextualization can create a barrier to accessibility when
there is a disconnect between the student's background experience and the
context chosen by the instructor. This can have a particular impact when the
contextualization is used in the process of assessing student learning. This
study investigates the types of words that cause difficulty for students. The
assessment shows that there are terms used on engineering tests that present
possible barriers for students, such that the test may in part be assessing the
student's cultural knowledge or vocabulary rather than engineering competency.
We propose a number of strategies for remediating this situation including the
use of hypertext to mitigate this type of accessibility barrier. Keywords: accessibility, adult education, assessment, contextualization, diversity,
engineering education, inclusivity, instruction, learning barrier, pedagogy,
universal instructional design | |||
| Assessing users' interactions for clustering web documents: a pragmatic approach | | BIBAK | Full-Text | 277-278 | |
| Luis A. Leiva; Enrique Vidal | |||
| In this paper we are interested in describing Web pages by how users
interact within their contents. Thus, an alternate but complementary way of
labelling and classifying Web documents is introduced. The proposed methodology
is founded on unsupervised learning algorithms, aiming to automatically find
natural clusters by means of users' implicit interaction data. Furthermore, it
also copes with the dynamic nature and heterogeneity of both users' behaviour
and the Web, updating the clustering model over time. We want to show that our
framework can be easily integrated in any Website, just employing already-known
methods and current technologies. Keywords: document profiling, implicit modelling, unsupervised learning, web mining | |||
| Discovery of information disseminators and receptors on online social media | | BIBAK | Full-Text | 279-280 | |
| Munmun De Choudhury | |||
| Today, there is significant sharing of information artifacts among users on
various social media sites, including Digg, Twitter and Flickr. An interesting
consequence of such rich and extensive social interaction is the evolving
nature of "roles" that are acquired by users over time, in the context of
variegated communication activities, such as commenting, replying, uploading a
media artifact and so on. In this paper, we investigate the discovery of two
roles that define information dissipation: disseminators and receptors. We
propose a computational framework based on factorization of stacked
representation of activities and test the outcomes on a dataset from Digg.
Experiments show that our approach can, interestingly, reveal correlations with
user activities occurring at a future point in time. Keywords: digg, information diffusion, information disseminators, information roles,
social media, social network analysis | |||
| Adaptation and search: from Dexter and AHAM to GAF | | BIBAK | Full-Text | 281-282 | |
| Evgeny Knutov; Paul De Bra; Mykola Pechenizkiy | |||
| Adaptive Hypermedia Systems (AHS) have long been concentrating on adaptive
guidance of links between domain concepts. Here we show parallels between
navigation and linking in adaptive hypermedia on the one hand and information
searching or querying on the other hand. We present a transition towards search
in AHS by aligning the web search process with the layered structure of AHS and
adaptation process. Keywords: adaptation, dexter model, navigation, open corpus, search | |||
| Brickstreams: physical hypermedia driven customer insight | | BIBAK | Full-Text | 283-284 | |
| Riddhiman Ghosh; Jhilmil Jain; Mohamed Dekhil | |||
| Brickstreams is a system that employs hypermedia structures in physical
spaces, specifically in brick-and-mortar retail environments, to capture
insight into customer behavior. By instrumenting and tracking interactions with
tagged products in retail stores, and by using demographic and location
intelligence, our system is able to bring the benefits of online clickstream
analysis to the brick and mortar world. We have implemented a prototype of
Brickstreams, realized through REST web services and mobile device clients. Keywords: clickstream analysis, customer insight, physical hypermedia | |||
| Collaborative identification and annotation of government deep web resources: a hybrid approach | | BIBAK | Full-Text | 285-286 | |
| Pengyi Zhang; Yan Qu; Chen Huang; Paul T. Jaeger; John Wells; W. Scott Hayes; James E. Hayes; Xin Jin | |||
| In this extended abstract, we propose a hybrid approach of automatic means
and social computing to identify and annotate Deep Web resources -- mainly
databases and database portals -- to provide easy access to and descriptions
and instruction on how to use these resources. Keywords: collaborative identification and annotation, government databases, hybrid
approach, social computing | |||
| Visual summaries of data: a spatial hypertext approach to user feedback | | BIBAK | Full-Text | 287-288 | |
| Annika L. Wolff; Paul Mulholland; Zdenek Zdrahal | |||
| In this paper we describe the SILVER toolkit, which is designed for tasks in
which a user learns by analysing and interpreting a set of resources. The user
categorises each resource according to the set of properties that they identify
as being applicable to it. Due to the large amount of data generated by this
type of task, the user may find it hard to identify patterns in their
classification and tagging, to recognise their own inconsistencies or make
comparisons between themselves and others. Principles of spatial hypertext can
be used to provide visual summaries of the data that can assist the above
activities. Keywords: categorisation, id3 decision trees, inquiry learning, organisation, spatial
hypertext | |||
| Dealing with the video tidal wave: the relevance of expertise for video tagging | | BIBAK | Full-Text | 289-290 | |
| Sara Darvish; Alvin Chin | |||
| The vast amounts of video that need to be tagged preclude the exclusive use
of professional indexers. Thus a significant amount of video will need to be
tagged by non-experts. Are the tags created by experts demonstrably superior to
those of non-experts, and when non-experts have to be used for tagging, is it
better to rely on tags created by those who upload videos or on others who
watch the videos? Two related studies were carried out, the first where domain
experts and others tagged videos, and the second where experts and others rated
the relevance of tags that had been assigned to videos in the first study.
Expert tags were judged to be more relevant by both experts and non-experts,
with non-expert viewers also creating significantly better tags than did owners
(i.e., the people who uploaded the videos). While significant differences were
observed, the mean overall judged relevance of tags was relatively low, even
for experts. Thus there seems to be considerable scope for the use of tag
recommendation systems and other tools that can make the tagging process more
consistent. Keywords: categorization, classification, collaborative tagging, tagging systems,
video annotation | |||
| Spatial contiguity and implicit learning in hypertext | | BIBAK | Full-Text | 291-292 | |
| Seungoh Paek; Daniel Hoffmann; Antonios Saravanos | |||
| The study is interested in how the spatial contiguity principle mediates
implicit learning in a hypertext environment. Keywords: hypertext, implicit learning, spatial contiguity | |||
| Objectivity classification in online media | | BIBAK | Full-Text | 293-294 | |
| Elisabeth Lex; Andreas Juffinger; Michael Granitzer | |||
| In this work, we assess objectivity in online news media. We propose to use
topic independent features and we show in a cross-domain experiment that with
standard bag-of-word models, classifiers implicitly learn topics. Our
experiments revealed that our methodology can be applied across different
topics with consistent classification performance. Keywords: classification, objectivity, online news media | |||
| Search your interests everywhere!: wikipedia-based keyphrase extraction from web browsing history | | BIBAK | Full-Text | 295-296 | |
| Mitsumasa Kondo; Akimichi Tanaka; Tadasu Uchiyama | |||
| This paper proposes a method that can extract user interests from the user's
Web browsing history. Our method allows easy access to multiple content domains
such as blogs, movies, QA sites, etc. since the user does not need to input a
separate search query in each domain/site. To extract user interests, the
method first extracts candidate keyphrases from the user's web browsed
documents. Second, important keyphrases obtained from a link structure analysis
of Wikipedia content is extracted from the main contents of web documents. This
technique is based on the idea that important keyphrases in Wikipedia are
important keyphrases in the real world. Finally, keyphrases contained in the
documents important to the user are set in order as user interests. An
experiment shows that our method offers improvements over a conventional method
and can recommend interests attractive to the user. Keywords: keyphrase extraction | |||
| On the robustness of google scholar against spam | | BIBAK | Full-Text | 297-298 | |
| Jöran Beel; Bela Gipp | |||
| In this research-in-progress paper we present the current results of several
experiments in which we analyzed whether spamming Google Scholar is possible.
Our results show, it is possible: We 'improved' the ranking of articles by
manipulating their citation counts and we made articles appear in searchers for
keywords the articles did not originally contained by placing invisible text in
modified versions of the article. Keywords: academic search engines, citation spam, search engines, spam, spamdexing | |||
| Leveraging multi-faceted tagging to improve search in folksonomy systems | | BIBAK | Full-Text | 299-300 | |
| Fabian Abel; Ricardo Kawase; Daniel Krause | |||
| In this paper we present ranking algorithms for folksonomy systems that
exploit additional contextual information attached to tag assignments
available. We evaluate the algorithms in the TagMe! system, a tagging front-end
for Flickr, and show that our algorithms, which exploit categories, spatial
information, and URIs describing the semantics of tag assignments, perform
significantly better than the FolkRank that does not consider such contextual
information. Keywords: context, faceted tagging, folksonomies, ranking, search, social media | |||
| Automatic extraction of structure, content and usage data statistics of web sites | | BIBAK | Full-Text | 301-302 | |
| Ioannis Paparrizos; Vassiliki Koutsonikola; Lefteris Angelis; Athena Vakali | |||
| In this paper we present a web mining tool which automatically extracts the
structure, content and usage data statistics of web sites. This work inspired
by the fact that web mining consists of three axes: web structure mining, web
content mining and web usage mining. Each one of those axes is using the
structure, content and usage data respectively. The scope is to use the
developed multi-thread web crawler as a tool to automatically extract from web
pages data that are associated with each one of those three axes in order
afterwards to compute several useful descriptive statistics and apply advanced
mathematical and statistical methods. A description of our system is provided
as well as some experimentation results. Keywords: classification algorithm, crawling, structure, content and usage data, web
mining | |||
| Enhancing search applications by utilizing mind maps | | BIBAK | Full-Text | 303-304 | |
| Jöran Beel; Bela Gipp | |||
| In this paper we present how sharing and utilizing mind maps could enhance
search applications such as document search engines and recommender systems. In
addition, we briefly present the first research results which indicate that
mind maps can be used to determine document relatedness and therefore can
enhance document recommender systems. We also discuss some challenges that
information retrieval on mind maps will probably have to overcome. Keywords: information retrieval, mind maps, search applications, social media | |||
| Crossmedia personalized learning contexts | | BIBAK | Full-Text | 305-306 | |
| Alcina Prata; Nuno Guimarães; Teresa Chambel | |||
| The trends in convergence, integration and co-existence of various media
technologies are creating new opportunities for the globalization of learning
practices. The emerging era of lifelong learning is calling for flexible
environments. Interactive television (iTV) holds a great potential in this
scenario, but there is still limited research in terms of cognitive and
interaction aspects. With the aim to link these opportunities, in flexible,
adequate and effective learning contexts, a new paradigm to generate crossmedia
personalized learning contexts from iTV, based on cognitive and affective
aspects, is being studied. This paper presents the results obtained from the
use of the e-iTV system, designed to illustrate and explore this paradigm. Keywords: crossmedia learning environments, educational hypermedia, human-computer
interaction, iTV, personalized web content | |||
| Webpage relationships for information retrieval within a structured domain | | BIBAK | Full-Text | 307-308 | |
| Vincent W. L. Tam; John Shepherd | |||
| In this paper, we describe a technique for improving the effectiveness of
information retrieval within individual websites. Our proposed approach
exploits the link structures within the site and the idea that relevant content
maybe spread across several related pages within the site. We present
experiments which compare our approach to other web search techniques. Keywords: domain specific search, hyperlink structure | |||
| Show my code in the web | | BIBAK | Full-Text | 309-310 | |
| Min-Jung Bae; Jeong-Hoon Ji; Gyun Woo | |||
| This paper proposes a method to show the code in the web in a very compact
way. The visualization method provides two pictures for a source code, each of
which is based on the Flower of Life and the Hilbert Curve. Each visualization
result captures the nesting structure and the size of the code. According to
the experiment, the complexity of the visualization has a signicant correlation
with the traditional software metrics. Keywords: flower of life, hilbert curve, source code, visualization, web service | |||
| Emberlight: share and publish spatial hypertext to the web | | BIBAK | Full-Text | 311-312 | |
| J. Nathan Matias; Frederick Cheung | |||
| Emberlight publishes spatial hypertext to the web, providing basic
versioning and collaboration for users of desktop spatial hypertext software.
In this demo session, we will seek feedback on the system, consider integration
collaborations, talk about new research avenues, and discuss funding ideas. Keywords: collaboration, comparison, shywiki, spatial hypertext, tinderbox, version
management, viki, vkb, vue | |||
| HVet: a hypervideo environment to support veterinary surgery learning | | BIBAK | Full-Text | 313-314 | |
| Claudio A. B. Tiellet; André Grahl Pereira; Eliseo Berni Reategui; José Valdeni Lima; Teresa Chambel | |||
| In this demo, we present HVet, a hypervideo environment to support learning
of veterinary surgery as an alternative to learning with live animals. By
adding structure and interactivity, hypervideo allows to navigate video and to
explore other related media to complement it, supporting the creation of a rich
and realistic learning environment, with interactive access, construction and
communication of knowledge. Keywords: design, high education, hypervideo, surgery, veterinary | |||
| Past visions of hypertext and their influence on us today | | BIBAK | Full-Text | 315 | |
| Darren Lunn; Mark Bernstein; Cathy Marshall; J. Nathan Matias; James M. Nyce; Frank Tompa | |||
| In July 1945, Vannevar Bush published the seminal paper As We May Think in
Atlantic Monthly [2]. In this paper Bush proposed MEMEX, a device where
information and records could be stored and linked together through 'trails'
and 'associations' rather than 'artificial' indexing mechanisms. This idea is
credited with being the inspiration, and precursor, for the modern World Wide
Web (WWW) invented by Tim Berners-Lee, but as Harper notes, for most of the
article, Bush was not concerned solely with the technical aspects of his MEMEX
system. Instead, as with most computer visionaries, he was more concerned with
how the computer system and its interfaces could help humanity [3]. We must
therefore consider if, as a research field, we are still trying to build MEMEX
as Bush envisioned it, or are we more influenced by a vision of information
storage and presentation, of which Bush's paper was one of many? Keywords: history, hypertext, memex | |||
| The social life of hypertext | | BIBAK | Full-Text | 317 | |
| Irene Greif | |||
| We live in a world where networks of people mingle with networks of
documents, creating networks of ideas that are linked to the people and
documents that subscribe to them. New tools are being created that facilitate
the interactions between these networks, greatly expanding the role of
hypertext as a social media tool. Interactive visualization is a particularly
powerful tool that capitalizes on the immense visual processing power of the
human brain. With Web 2.0 and related technologies the world of ideas is being
shaped by the wisdom of crowds. People understand data better when we scale up
the audience. While one can learn a lot simply watching visual displays of
information, there is also a pent up desire to analyze. People want their own
controls, so that they can see data in their own way by looking at it
differently. ManyEyes is a system that features a range of visualizations,
where people can upload data and see that data in a variety of ways. When
people find interesting views of the data they can annotate them and share
their comments with others, thus building a community around visualization and
interpretation. Sharing visualizations and interpretations lets people have
deeper discussions in the communities that they belong to, facilitating
conversations on politics, economics, health, and a host of other issues. We
have found that visualizations are particularly powerful when used to analyze
words. Dynamic visualizations draw people in and lead to interesting new
conclusions. Scalable real world deployments let research keep up with the
wisdom of crowds, and this keynote will explore some of the emerging research
in this area. More information about the Many Eyes project can be found at
www.many-eyes.com. Keywords: collaboration, text analysis, visualization, web 2.0 | |||