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UMAP Tables of Contents: 00010203040506070809101112131415

Proceedings of AH 2008 Adaptive Hypermedia and Adaptive Web-based Systems 2008-07-29

Fullname:Proceedings of the 5th International Conference on Adaptive Hypermedia and Adaptive Web-Based Systems
Editors:Wolfgang Nejdl; Judy Kay; Pearl Pu; Eelco Herder
Location:Hannover, Germany
Dates:2008-Jul-29 to 2008-Aug-01
Series:Lecture Notes in Computer Science, 2008, Volume 5149
Standard No:ISBN: 978-3-540-70984-8; hcibib: UMAP08
Links:Online Proceedings | Conference Home Page
Summary:The Adaptive Hypermedia conferences are the major forums for the scientific exchange and presentation of research on adaptive hypermedia and adaptive Web-based systems. This year's fifth edition of the conference will be organized by the L3S Research Center in the city of Hannover, Germany.The 2008 conference is momentous, as it represents the marriage of the Adaptive Hypermedia and User Modeling communities, both of which are major sponsors.
  1. Keynote Speakers
  2. Full Papers
  3. Short Papers
  4. Demo Papers
  5. Doctoral Consortium

Keynote Speakers

Baroque Technology BIBAFull-Text 1-5
  Jan Borchers
As new interactive systems evolve, they frequently hit a sweet spot: A few new tricks to learn, and users gets tremendous benefits, simplifying their lives. But beyond that lies the dark phase of baroque technology: increasing complexity with little payoff. We will look at examples for both sweet-spot and baroque interactive technologies, from GPS devices to window systems, find out how to identify each kind, and become better interaction designers in the process.
Adaptive Navigation Support for Open Corpus Hypermedia Systems BIBAKFull-Text 6-8
  Peter Brusilovsky
Open corpus adaptive hypermedia could be considered one of the major challenges of the adaptive hypermedia community since it can dramatically extend the range of applicability of adaptive hypermedia systems. An open corpus adaptive hypermedia system can be defined in as an "adaptive hypermedia system which operates on an open corpus of documents, e.g., a set of documents that is not known at design time and, moreover, can constantly change and expand" [6]. For the last five years open corpus adaptive hypermedia has been one of the priorities of our research group at the University of Pittsburgh. The goal of this presentation is to discuss the problems of open corpus adaptive hypermedia, review major approaches for developing adaptive navigation support for open corpus AHS system, and report our experience with some of these approaches.
Keywords: Adaptive navigation support; adaptive hypermedia; open corpus
Altruism, Selfishness, and Destructiveness on the Social Web BIBAFull-Text 9-11
  John Riedl
Many online communities are emerging that, like Wikipedia, bring people together to build community-maintained artifacts of lasting value (CALVs). What is the nature of people's participation in building these repositories? What are their motives? In what ways is their behavior destructive instead of constructive? Motivating people to contribute is a key problem because the quantity and quality of contributions ultimately determine a CALV's value. We pose three related research questions: 1) How does intelligent task routing -- matching people with work -- affect the quantity of contributions? 2) How does reviewing contributions before accepting them affect the quality of contributions? 3) How do recommender systems affect the evolution of a shared tagging vocabulary among the contributors? We will explore these questions in the context of existing CALVs, including Wikipedia, Facebook, and MovieLens.

Full Papers

A Rule-Based Recommender System for Online Discussion Forums BIBAFull-Text 12-21
  Fabian Abel; Ig Ibert Bittencourt; Nicola Henze; Daniel Krause; Julita Vassileva
In this paper we present a rule-based personalization framework for encapsulating and combining personalization algorithms known from adaptive hypermedia and recommender systems. We show how this personalization framework can be integrated into existing systems by example of the educational online board Comtella-D, which exploits the framework for recommending relevant discussions to the users. In our evaluations we compare different recommender strategies, investigate usage behavior over time, and show that a small amount of user data is sufficient to generate precise recommendations.
Locally Adaptive Neighborhood Selection for Collaborative Filtering Recommendations BIBAFull-Text 22-31
  Linas Baltrunas; Francesco Ricci
User-to-user similarity is a fundamental component of Collaborative Filtering (CF) recommender systems. In user-to-user similarity the ratings assigned by two users to a set of items are pairwise compared and averaged (correlation). In this paper we make user-to-user similarity adaptive, i.e., we dynamically change the computation depending on the profiles of the compared users and the target item whose rating prediction is sought. We propose to base the similarity between two users only on the subset of co-rated items which best describes the taste of the users with respect to the target item. These are the items which have the highest correlation with the target item. We have evaluated the proposed method using a range of error measures and showed that the proposed locally adaptive neighbor selection, via item selection, can significantly improve the recommendation accuracy compared to standard CF.
Adaptive Retrieval of Semi-structured Data BIBAFull-Text 32-41
  Yosi Ben-Asher; Shlomo Berkovsky; Paolo Busetta; Yaniv Eytani; Sadek Jbara; Tsvi Kuflik
The rapidly growing amount of heterogeneous semi-structured data available on the Web is creating a need for simple and universal access methods. For this purpose, we propose exploiting the notion of UNSpecified Ontology (UNSO), where the data objects are described using a list of attributes and their values. To facilitate efficient management of UNSO data objects, we use LoudVoice, a multi-agent channeled multicast communication platform, where each attribute is assigned a designated communication channel. This allows efficient searches to be performed by querying only the relevant channels, and aggregating the partial results. We implemented a prototype system and experimented with a corpus of real-life E-Commerce advertisements. The results demonstrate that the proposed approach yields a high level of accuracy and scalability.
Using Collaborative Models to Adaptively Predict Visitor Locations in Museums BIBAFull-Text 42-51
  Fabian Bohnert; Ingrid Zukerman; Shlomo Berkovsky; Timothy Baldwin; Liz Sonenberg
The vast amounts of information presented in museums can be overwhelming to a visitor, whose receptivity and time are typically limited. Hence, s/he might have difficulties selecting interesting exhibits to view within the available time. Mobile, context-aware guides offer the opportunity to improve a visitor's experience by recommending exhibits of interest, and personalising the delivered content. The first step in this recommendation process is the accurate prediction of a visitor's activities and preferences. In this paper, we present two adaptive collaborative models for predicting a visitor's next locations in a museum, and an ensemble model that combines their predictions. Our experimental results from a study using a small dataset of museum visits are encouraging, with the ensemble model yielding the best performance overall.
Supporting Users in Creating Pedagogically Sound Personalised Learning Objects BIBAKFull-Text 52-61
  Aoife Brady; Owen Conlan; Vincent Wade; Declan Dagger
Successful eLearning is predicated on the application of pedagogies appropriate to online education that respond to the capabilities and needs of the learners. Typically, designing and assembling personalized learning objects that respond to the pedagogical needs of a variety of different learners is an expensive and time-consuming process requiring both domain and educational expertise. Educators have the domain expertise and formal or informal pedagogical knowledge to create quality learning objects. However, they lack the tools and often the specific knowledge of online pedagogical approaches that make it time efficient for them to do so. This paper describes the motivation behind, the workflow supported by and the evaluation of the LO Generator, a tool that offers personalized support and scaffolding for users, who are not necessarily content creation or pedagogical experts, in assembling pedagogically sound personalized learning objects.
Keywords: Personalization; Pedagogy; eLearning; Learning Object Creation
Supporting Interaction Preferences and Recognition of Misconceptions with Independent Open Learner Models BIBAFull-Text 62-72
  Susan Bull; Andrew Mabbott; Peter Gardner; Tim Jackson; Michael J. Lancaster
Misconceptions have been identified in many subjects. However, there has been less investigation into students' interest in their misconceptions. This paper presents two independent open learner models used alongside seven university courses to highlight the state of their knowledge to the learner as a starting point for their independent study. Many students used the environments; many had misconceptions identified at some point during their learning; and most of those with misconceptions viewed the statements of their misconceptions. Students were able to use the independent open learner models in a variety of ways to suit their interaction preferences, at different levels of study.
An Evidence-Based Approach to Handle Semantic Heterogeneity in Interoperable Distributed User Models BIBAFull-Text 73-82
  Francesca Carmagnola; Vania Dimitrova
Nowadays, the idea of personalization is regarded as crucial in many areas. This requires quick and robust approaches for developing reliable user models. The next generation user models will be distributed (segments of the user model will be stored by different applications) and interoperable (systems will be able to exchange and use user model fractions to enrich user experiences). We propose a new approach to deal with one of the key challenges of interoperable distributed user models -- semantic heterogeneity. The paper presents algorithms to automate the user model exchange across applications based on evidential reasoning and advances in the Semantic Web.
Concept-Based Document Recommendations for CiteSeer Authors BIBAKFull-Text 83-92
  Kannan Chandrasekaran; Susan Gauch; Praveen Lakkaraju; Hiep Phuc Luong
The information explosion in today's electronic world has created the need for information filtering techniques that help users filter out extraneous content to identify the right information they need to make important decisions. Recommender systems are one approach to this problem, based on presenting potential items of interest to a user rather than requiring the user to go looking for them. In this paper, we propose a recommender system that recommends research papers of potential interest to authors known to the CiteSeer database. For each author participating in the study, we create a user profile based on their previously published papers. Based on similarities between the user profile and profiles for documents in the collection, additional papers are recommended to the author. We introduce a novel way of representing the user profiles as trees of concepts and an algorithm for computing the similarity between the user profiles and document profiles using a tree-edit distance measure. Experiments with a group of volunteers show that our concept-based algorithm provides better recommendations than a traditional vector-space model based technique.
Keywords: Recommender System; CiteSeer; Digital Library; Conceptual Recommender
Social Information Access for the Rest of Us: An Exploration of Social YouTube BIBAFull-Text 93-102
  Maurice Coyle; Jill Freyne; Peter Brusilovsky; Barry Smyth
The motivation behind many Information Retrieval systems is to identify and present relevant information to people given their current goals and needs. Learning about user preferences and access patterns recent technologies make it possible to model user information needs and adapt services to meet these needs. In previous work we have presented ASSIST, a general-purpose platform which incorporates various types of social support into existing information access systems and reported on our deployment experience in a highly goal driven environment (ACM Digital Library). In this work we present our experiences in applying ASSIST to a domain where goals are less focused and where casual exploration is more dominant; YouTube. We present a general study of YouTube access patterns and detail how the ASSIST architecture affected the access patterns of users in this domain.
(Web Search)shared: Social Aspects of a Collaborative, Community-Based Search Network BIBAFull-Text 103-112
  Maurice Coyle; Barry Smyth
Collaborative Web search (CWS) is a community-based approach to Web search that supports the sharing of past result selections among a group of related searchers so as to personalize result-lists to reflect the preferences of the community as a whole. In this paper, we present the results of a recent live-user trial which demonstrates how CWS elicits high levels of participation and how the search activities of a community of related users form a type of social search network.
Evaluation of ACTSim: A Composition Tool for Authoring Adaptive Soft Skill Simulations BIBAKFull-Text 113-122
  Conor Gaffney; Declan Dagger; Vincent Wade
Adaptivity in technology enhanced learning has proven to be an effective and efficient approach in education. While simulations are include in the top end of eLearning there has been few if any real attempts to develop adaptive educational simulations. The key problem with their incorporation is their expense, cost and the effort involved in developing them. This ground breaking paper is the first publication to show a unique way for non-technical domain experts to compose and generate adaptive eLearning simulations. In particular it presents ACTSim, an innovative and unique composition tool used to author adaptive soft skill simulations.
Keywords: composition; simulation; education; soft skills
Modelling Semantic Relationships and Centrality to Facilitate Community Knowledge Sharing BIBAKFull-Text 123-132
  Styliani Kleanthous; Vania Dimitrova
Some of today's most widely spread applications are social systems where people can form communities and share knowledge. However, knowledge sharing is not always effective and communities often do not sustain. Can user modelling approaches help to identify what support could be offered and how this would benefit the community? The paper presents algorithms for extracting a model of a closely-knit virtual community following processes identified as important for effective communities. The algorithms are applied to get an insight of a real virtual community and to identify what support may be needed to help the community function better as an entity.
Keywords: Knowledge Sharing; Community Model; Community Adaptation
LS-Plan: An Effective Combination of Dynamic Courseware Generation and Learning Styles in Web-Based Education BIBAFull-Text 133-142
  Carla Limongelli; Filippo Sciarrone; Giulia Vaste
This paper presents LS-Plan, a system capable of providing Educational Hypermedia with adaptation and personalization. The architecture of LS-Plan is based on three main components: the Adaptation Engine, the Planner and the Teacher Assistant. Dynamic course generation is driven by an adaptation algorithm, based on Learning Styles, as defined by Felder-Silverman's model. The Planner, based on Linear Temporal Logic, produces a first Learning Objects Sequence, starting from the student's Cognitive State and Learning Styles, as assessed through pre-navigation tests. During the student's navigation, and on the basis of learning assessments, the adaptation algorithm can propose a new Learning Objects Sequence. In particular, the algorithm can suggest different learning materials either trying to fill possible cognitive gaps or by re-planning a newly adapted Learning Objects Sequence. A first experimental evaluation, performed on a prototype version of the system, has shown encouraging results.
Pervasive Personalisation of Location Information: Personalised Context Ontology BIBAKFull-Text 143-152
  William T. Niu; Judy Kay
There is considerable value in personalising information about people's location. Personalised Context Ontology (PECO) is an ontology for a building, and with PECO, we can provide personalised descriptions of the relevant people. For pragmatic reasons, it is important that PECO is created semi-automatically, making flexible use of a range of sources. For reasons of user control, it is important that PECO can be used to explain the personalisation. This paper describes PECO and how it is created for reasoning about a building. We also describe its use in an application called Locator, which presents information about the people in a building. PECO enables Locator to provide personalised information in two ways: it shows people of relevance and it makes use of personalised location labels. At the same time, PECO enables the user to scrutinise the reasoning about the personalisation. We report a study with eight users in which we compare a personalised and a non-adaptive versions of Locator. This indicates that people preferred the personalised version even though they could complete the designed tasks with both systems.
Keywords: personal ontology; ontological reasoning; personalised location label; scrutability
Using Decision Models for the Adaptive Generation of Learning Spaces BIBAKFull-Text 153-162
  Eric Ras; Dimitri Ilin
This paper presents an approach that uses a decision model for resolving variations in a so-called learning space, which aim is to enhance the reuse of explicitly documented experiences by providing context-aware learning content. Decision models promise a better possibility to separate the variabilities in e-learning content, and address the problem of closed corpus of adaptive hypermedia systems. Adaptation is not coupled to a fixed set of learning resources, but to types of learning space concepts. The system adapts and personalizes the learning space to the learner's situation. A controlled experiment provides first statistically significant results, which show an experience package reuse improvement regarding knowledge acquisition and application efficiency. Further, it provides a baseline for future evaluations of different adaptation methods and techniques.
Keywords: adaptation; decision model; experience management; learning space
Accuracy in Rating and Recommending Item Features BIBAFull-Text 163-172
  Lloyd Rutledge; Natalia Stash; Yiwen Wang; Lora Aroyo
This paper discusses accuracy in processing ratings of and recommendations for item features. Such processing facilitates feature-based user navigation in recommender system interfaces. Item features, often in the form of tags, categories or meta-data, are becoming important hypertext components of recommender interfaces. Recommending features would help unfamiliar users navigate in such environments. This work explores techniques for improving feature recommendation accuracy. Conversely, it also examines possibilities for processing user ratings of features to improve recommendation of both features and items.
   This work's illustrative implementation is a web portal for a museum collection that lets users browse, rate and receive recommendations for both artworks and interrelated topics about them. Accuracy measurements compare proposed techniques for processing feature ratings and recommending features. Resulting techniques recommend features with relative accuracy. Analysis indicates that processing ratings of either features or items does not improve accuracy of recommending the other.
Does 'Notice' Prompt Noticing? Raising Awareness in Language Learning with an Open Learner Model BIBAFull-Text 173-182
  Gheida Shahrour; Susan Bull
Open learner models (OLM) are learner models that are accessible to the learner they represent. Many examples now exist, often with the aim of prompting learner reflection on their knowledge. In language learning, this relates to research on noticing and awareness-raising. We here introduce an open learner model to investigate the potential of OLMs to facilitate noticing. Results suggest that an OLM could be a useful way of helping students to notice language features, with all students noticing some of the features tested, a result that was maintained in a delayed post-test one week after the experimental session.
Proactive Versus Multimodal Online Help: An Empirical Study BIBAKFull-Text 183-192
  Jérôme Simonin; Noëlle Carbonell
Two groups of 8 participants experimented two enhancements of standard online help for the general public during one hour: adaptive proactive (AP) assistance and multimodal user support. Proactive help, that is, anticipation of the user's information needs raised very positive judgments, while dynamic adaptation to the user's current knowledge and skills went almost unnoticed. Speech and graphics (SG) messages were also well accepted, based on the observation that one can go on interacting with the software application while listening to instructions. However, several participants observed that the transience and linearity of speech limited the usability of this modality. Analysis of interaction logs and post-tests shows that procedural and semantic knowledge acquisition was higher with SG help than with AP assistance. Contrastingly, AP help was consulted more often than SG user support. Results also suggest that proactive online help may reduce the effectiveness of autonomous "learning by doing" acquisition of unfamiliar software concepts and procedures.
Keywords: Online help; Adaptive user interfaces; Proactive user support; Multimodal interaction; Speech and graphics help messages
Re-assessing the Value of Adaptive Navigation Support in E-Learning Context BIBAFull-Text 193-203
  Sergey Sosnovsky; Peter Brusilovsky; Danielle H. Lee; Vladimir Zadorozhny; Xin Zhou
In a recent study, we discovered a new effect of adaptive navigation support in the context of E-learning: the ability to motivate students to work more with non-mandatory educational content. The results presented in this paper extend the limits of our earlier findings. We describe the implementation of adaptive navigation support for the SQL domain, and report the results of the classroom evaluation of our approach. Among other issues, we investigate whether the use in parallel of two different types of navigation support could change the nature or the magnitude of the previously observed effect. Our study confirms the motivational value of navigation support in the new domain. We observe the increase of this effect after adding the concept-based navigation layer to the existing topic-based adaptive navigation service. The results of the navigational pattern analysis allow us to determine the major source of this increase.
The Effectiveness of Personalized Movie Explanations: An Experiment Using Commercial Meta-data BIBAFull-Text 204-213
  Nava Tintarev; Judith Masthoff
This paper studies the properties of a helpful and trustworthy explanation in a movie recommender system. It discusses the results of an experiment based on a natural language explanation prototype. The explanations were varied according to three factors: degree of personalization, polarity and expression of unknown movie features. Personalized explanations were not found to be significantly more Effective than non-personalized, or baseline explanations. Rather, explanations in all three conditions performed surprisingly well. We also found that participants evaluated the explanations themselves most highly in the personalized, feature-based condition.
User-Centric Profiling on the Basis of Cognitive and Emotional Characteristics: An Empirical Study BIBAKFull-Text 214-223
  Nikos Tsianos; Zacharias Lekkas; Panagiotis Germanakos; Costas Mourlas; George Samaras
In order to clarify whether extending learners' profiles in an adaptive educational system to cognitive and emotional characteristics may have a positive effect on performance, we conducted an empirical study that consists of two subsequent experiments. The human factors that were taken into consideration in the personalization process were cognitive style, visual working memory span, control/speed of processing and anxiety. With the exception of control/speed of processing, matching the instructional style to users' characteristics was revealed to be statistically significant in optimizing their performance (n=219). On the basis of this empirical assessment, this paper argues that individual differences at this intrinsic level are important, and their main effect can be manipulated by taking advantage of adaptive technologies.
Keywords: Cognitive style; working memory; anxiety; e-learning; personalization; user profiling
Towards Computerized Adaptive Assessment Based on Structured Tasks BIBAFull-Text 224-234
  Jozef Tvarozek; Miloš Kravcík; Mária Bieliková
In an attempt to support traditional classroom assessment processes with fully computerized methods, we have developed a method for adaptive assessment suitable for well structured domains with high emphasis on problem solving and capable of robust continuous assessment, potentially encouraging student's achievements, reflective thinking, and creativity. The method selects problems according to the student's demonstrated ability, structured task description schemes allow for a detailed analysis of student's errors, and on-demand generation of task instances facilitates independent student work. We evaluated the proposed method using a software system we had developed in the domain of middle school mathematics.
Adaptation of Elaborated Feedback in e-Learning BIBAKFull-Text 235-244
  Ekaterina Vasilyeva; Mykola Pechenizkiy; Paul De Bra
Design of feedback is a critical issue of online assessment development within Web-based Learning Systems (WBLSs). In our work we demonstrate the possibilities of tailoring the feedback to the students' learning style (LS), certitude in response and its correctness. We observe in the experimental studies that these factors have a significant influence on the feedback preferences of students and the effectiveness of elaborated feedback (EF), i.e. students' performance improvement during the test. These observations helped us to develop a simple EF recommendation approach. Our experimental study shows that (1) many students are eager to follow the recommendations on necessity to read certain EF in the majority of cases; (2) the students more often find the recommended EF to be useful, and (3) the recommended EF helped to answer related questions better.
Keywords: feedback authoring; feedback personalization; online assessment
Adaptive Link Annotation in Distributed Hypermedia Systems: The Evaluation of a Service-Based Approach BIBAKFull-Text 245-254
  Michael Yudelson; Peter Brusilovsky
A service-based approach to link annotation expands the applicability of adaptive navigation support functionality beyond the limits of traditional adaptive hypermedia systems. With this approach, the decision-making functionality is separated from the application systems and encapsulated in a personalization service. This paper attempts to evaluate the feasibility of using this approach in the real world. After a brief overview of current efforts to develop service-based approaches to adaptive hypermedia, we describe our specific implementation of this approach as personalization architecture and report the results of an extensive performance evaluation of this architecture.
Keywords: Adaptive navigation support; adaptive annotation; personalization; service; distributed architecture

Short Papers

Do Students Trust Their Open Learner Models? BIBAFull-Text 255-258
  Norasnita Ahmad; Susan Bull
Open learner models (OLM) enable users to access their learner model to view information about their understanding. Opening the learner model to the learner may increase their perceptions of how a system evaluates their knowledge and updates the model. This raises questions of trust relating to whether the learner believes the evaluations are correct, and whether they trust the system as a whole. We investigate learner trust in various OLM features: the complexity of the model presentation; the level of learner control over the model contents; and the facility to release one's own model for peer viewing.
A Framework for the Development of Distributed, Context-Aware Adaptive Hypermedia Applications BIBAFull-Text 259-262
  Liliana Ardissono; Anna Goy; Giovanna Petrone
The CAWE framework supports the development of context-aware, Service Oriented applications which integrate heterogeneous services and customize the cooperation among multiple users. We present the techniques adopted in the framework to manage a context-sensitive interaction with the users.
Collection Browsing through Automatic Hierarchical Tagging BIBAFull-Text 263-266
  Korinna Bade; Marcel Hermkes
In order to navigate huge document collections efficiently, tagged hierarchical structures can be used. For users, it is important to correctly interpret tag combinations. In this paper, we propose the usage of tag groups for addressing this issue and an algorithm that is able to extract these automatically for text documents. The approach is based on the diversity of content in a document collection. For evaluation, we use methods from ontology evaluation and showed the validity of our approach on a benchmark dataset.
Aspect-Based Personalized Text Summarization BIBAFull-Text 267-270
  Shlomo Berkovsky; Timothy Baldwin; Ingrid Zukerman
This work investigates user attitudes towards personalized summaries generated from a coarse-grained user model based on document aspects. We explore user preferences for summaries at differing degrees of fit with their stated interests, the impact of length on user ratings, and the faithfulness of personalized and general summaries.
What Can I Watch on TV Tonight? BIBAFull-Text 271-274
  David Bueno; Ricardo Conejo; David Martín; Jorge León; Javier G. Recuenco
This paper presents the methods used in a TV Recommender System that helps users in the difficult task of finding an interesting TV program from among the hundreds of channels that we can find nowadays on TV. Our aim is to cover not only user preferences but also user restrictions while watching TV. The recommendations use a hybrid method, combining content based and folksonomy (collaborative and social recommendations). We also present interesting initial results of some experiments that try to show the accuracy of the users recommendations.
Adaptive Navigation Support, Learner Control and Open Learner Models BIBAFull-Text 275-278
  Susan Bull; Norasnita Ahmad; Matthew Johnson; Rasyidi Johan; Andrew Mabbott
We consider open learner models (OLM) with reference to adaptive navigation support and learner control. Our purpose is to assess the potential of a greater range of OLMs in adaptive educational hypermedia. We introduce five OLMs, discuss how these might be applied, and present learner reactions.
News@hand: A Semantic Web Approach to Recommending News BIBAKFull-Text 279-283
  Iván Cantador; Alejandro Bellogín; Pablo Castells
We present News@hand, a news recommender system which applies semantic-based technologies to describe and relate news contents and user preferences in order to produce enhanced recommendations. The exploitation of conceptual information describing contents and user profiles, along with the capability of inferring knowledge from the semantic relations defined in the ontologies, enabling different content-based collaborative recommendation models, are the key distinctive aspects of the system. The multi-domain portability, the multi-media source applicability, and addressing of some limitations of current recommender systems are the main benefits of our proposed approach.
Keywords: recommender systems; ontologies; personalisation; user modelling; group modelling; semantic web
A SOA-Based Framework to Support User Model Interoperability BIBAFull-Text 284-287
  Federica Cena; Roberto Furnari
This paper presents an approach to achieve User Model (UM) interoperability exploiting Web Service technologies for syntactic interoperability, and Semantic Web languages for semantic interoperability, together with negotiation techniques based on dialogue. We propose a SOA-based framework where a central UDDI registry, enhanced with UM specific capabilities, is used to support and promote the cooperation between UM-based applications.
Integrated Speaker Classification for Mobile Shopping Applications BIBAFull-Text 288-291
  Michael Feld; Gerrit Kahl
This paper presents an approach to how speaker classification can be used to enable new ways for recommender systems in a mobile shopping environment to bootstrap user models and avoid common problems such as the "early rater". In a concrete shopping scenario, we introduce the speech-controlled Mobile ShopAssist demonstrator that allows a new customer to more quickly find a product that fulfills his or her demographic group's specific requirements by exploiting features extracted from speech using the Agender speaker classification system. We propose a method for computing preference scores based on the user's profile and demonstrate how the application's GUI can be adapted to deliver the recommendations to the user.
The Authoring Tool of ADULT: Adaptive Understanding and Learning Text Environment BIBAKFull-Text 292-295
  Alexandra Gasparinatou; Grammatiki Tsaganou; Maria Grigoriadou
Previous research in the domain of text comprehension in Informatics has demonstrated that readers with little knowledge in this domain benefit from a coherent text, whereas high-knowledge readers benefit from a minimally coherent text. With respect to educational applications, these findings suggest constructing several versions of a text in order to adapt to varying levels of knowledge among readers. In this paper we present the design of the authoring tool of the learning environment ADULT (Adaptive Understanding and Learning from Texts), capable of supporting authors while constructing texts of different coherence in the domain of Informatics, accompanied by questions or tasks designed to access students' comprehension on line. This way students will be activated to use their background knowledge while reading and more students will have the opportunity to achieve better learning results in learning from Informatics texts than reading a single textbook in Informatics targeted at an average reader.
Keywords: Adaptive environment; Authoring tool supporting adaptive environment; Understanding and learning from texts; Background knowledge
Interoperability between MOT and Learning Management Systems: Converting CAF to IMS QTI and IMS CP BIBAKFull-Text 296-299
  Fawaz Ghali; Alexandra I. Cristea
The chain of applying adaptivity to Learning Management Systems (LMS) is still deficient; there is a gap between authoring adaptive materials and delivering them in LMS. In this paper, we extend My Online Teacher (MOT), an adaptive authoring system, by adding compatibility with IMS Question & Test Interoperability (QTI) and IMS Content Packaging (CP). Thus, the authors can utilize the authored materials for learning process adaptation on any standards-compatible LMS. From a technical perspective, we initialize the creation of adaptive LMS by converting Common Adaptation Format (CAF), XML representation of MOT database, into IMS QTI and IMS CP, to ensure a wider uptake and use of adaptive learning systems. Finally, this work represents a significant step towards the little explored avenue of adaptive collaborative systems based on extant learning standards and popular LMS.
Keywords: Adaptive authoring; MOT; LMS; IMS QTI; IMS CP
Proactively Adapting Interfaces to Individual Users for Mobile Devices BIBAFull-Text 300-303
  Melanie Hartmann; Daniel Schreiber
The amount of functionality offered by nowadays applications is constantly growing, mostly leading to more and more complex user interfaces. This often decreases their usability, especially in mobile settings where we have to deal with limited input and output capabilities. We state that adapting the interface to the available devices as well as to the user's current needs is the key to improving usability. In this paper, we present the AUGUR system that can automatically generate user- and device-adapted interfaces. We thereby focus on the FxL* algorithm that determines which user interface elements are currently relevant for a user. We show that it clearly outperforms algorithms that do not take the user or her situation into account.
Reuse Patterns in Adaptation Languages: Creating a Meta-level for the LAG Adaptation Language BIBAKFull-Text 304-307
  Maurice Hendrix; Alexandra I. Cristea
A growing body of research targets authoring of content and adaptation strategies for adaptive systems. The driving force behind it is semantics-based reuse: the same strategy can be used for various domains, and vice versa. Whilst using an adaptation language (LAG e.g.) to express reusable adaptation strategies, we noticed, however, that: a) the created strategies have common patterns that, themselves, could be reused; b) templates based on these patterns could reduce the designers' work; c) there is a strong preference towards XML-based processing and interfacing. This has leaded us to define a new meta-language for LAG, extracting common design patterns. This paper provides more insight into some of the limitations of Adaptation Languages like LAG, as well as describes our meta-language, and shows how introducing the meta-level can overcome some redundancy issues.
Keywords: LAG; AHA!; Adaptive Hypermedia; Adaptation Engine
Implementing a Multimodal Interface to a DITA User Assistance Repository BIBAKFull-Text 308-311
  Aidan Kehoe; Ian Pitt
User assistance systems can be extended to enable multimodal access to user assistance material. Implementing multimodal user assistance introduces new considerations with respect to authoring and storage of assistance material, transformation of assistance material for effective presentation on a range of devices, and user interaction issues. We describe an implementation of a multimodal interface to enable access to a DITA user assistance repository.
Keywords: User Assistance; DITA; Multimodal Interface
Analysing High-Level Help-Seeking Behaviour in ITSs BIBAFull-Text 312-315
  Moffat Mathews; Tanja Mitrovic; David Thomson
In this paper, we look at initial results of data mining students' help-seeking behaviour in two ITSs: SQL-Tutor and EER-Tutor. We categorised help given by these tutors into high-level (HLH) and low-level help (LLH), depending on the amount of help given. Each student was grouped into one of ten groups based on the frequency with which they used HLH. Learning curves were then plotted for each group. We asked the question, "Does a student's help-seeking behaviour (especially the frequency with which they use HLH) affect learning?" We noticed similarities between results for both tutors. Students who were very frequent users of HLH showed the lowest learning, both in learning rates and depth of knowledge. Students who were low to medium users of HLH showed the highest learning rates. Least frequent users of HLH had lower learning rates but showed higher depth of knowledge and a lower initial error rate, suggesting higher initial expertise. These initial results could suggest favouring pedagogical strategies that provide low to medium HLH to certain students.
Data-Driven Prediction of the Necessity of Help Requests in ILEs BIBAFull-Text 316-319
  Manolis Mavrikis
This paper discusses the data-driven development of a model which predicts whether a student could answer a question correctly without requesting help. This model contributes to a broader piece of research, the primary goal of which was to predict affective characteristics of students working in ILEs. The paper presents the Bayesian network which provides adequate predictions, and discusses how its accuracy is taken into account when the model is integrated in an ILE. Future steps to improve the results are briefly discussed.
A Dynamic Content Generator for Adaptation in Hypermedia Systems BIBAKFull-Text 320-323
  David Mérida; Ramón Fabregat; Xavier Prat; David Huerva; Jeimy Velez
The heterogeneity problem (in terms of different types of access devices, network bandwidth, preferences/characteristics of the user, etc.) has become a major problem for the Internet. Different alternatives have been developed to allow universal access to any type of content. Adaptive Hypermedia Systems (AHS) have emerged as a solution for this. In previous works we proposed the SHAAD model, which includes the concepts of adaptability, adaptivity and dynamism to adapt web contents. Based on this model we implemented MAS-SHAAD, a multiagent system implementation of SHAAD. In this work we present the design and development of a dynamic content generator that can be added to any JAVA AHS implementation, such as MAS-SHAAD. The structure of the generator is defined by an ontology; therefore, a standard behavior can be obtained for any object included in the web pages generated and stored in the content repository.
Keywords: Adaptive hypermedia systems; multiagent systems; user modeling; device independency; heterogeneity; decision engine
Automatic Generation of User Adapted Learning Designs: An AI-Planning Proposal BIBAKFull-Text 324-328
  Lluvia Morales; Luis Castillo; Juan Fernandez-Olivares; Arturo Gonzalez-Ferrer
A Learning Design (LD) definition under the IMS-LD standard is a complex task for the instructor because it requires a lot of time, effort and previous knowledge of the students group over which will be defined the knowledge objectives. That is why, taking advantage from diffusion of learning objects (LO) labeling using IMS-MD standard, we have proposed to realize a knowledge engineering process, represented as an algorithm, over LO labels and user profiles to automatically define a domain that will be used by an intelligent planner to build a LD. This LD will be finally implemented in the ILIAS Learning Management System (LMS).
Keywords: Planning and Scheduling; e-learning; IMS standars; Automatic Generation of Planning Domains
Guaranteeing the Correctness of an Adaptive Tutoring System BIBAFull-Text 329-332
  Pilar Prieto-Linillos; Sergio Gutiérrez; Abelardo Pardo; Carlos Delgado Kloos
This paper presents an approach to create adaptive web-based educative systems that can be automatically audited by means of standard web testing tools. The auditing tool takes the role of a learner interacting with the system, checking that no errors are present. The tool can communicate with the exercises to know the correct answers to them; a configurable ratio of correct to incorrect answers allows the tool to behave as a range of different students. More complex checking techniques will be tested in the future using this architecture.
Designing a Personalized Semantic Web Browser BIBAKFull-Text 333-336
  Melike Sah; Wendy Hall; David C. De Roure
Web browsing is a complex activity and in general, users are not guided during browsing. Our hypothesis is that by using Semantic Web technologies and personalization methods, browsing can be supported better. However, existing personalization mechanisms on the Web are obstructive; users need to log in to multiple websites and enter their personal information and preferences, and the profiles are different for each site. There is a need for generic user profiles, which can also support the user's browsing. In this paper, we propose a novel Semantic Web browser using an ontology-driven user modeling architecture to enable semantic and adaptive links. We also introduce a new behavior-based user model. With our approach, users need to log in to their Web browser only and personalization is achieved on different websites.
Keywords: Semantic Web Browser; Semantic Web; User Modeling; Ontology; Personalization
Towards Inferring Sequential-Global Dimension of Learning Styles from Mouse Movement Patterns BIBAFull-Text 337-340
  Danilo Spada; Manuel Sánchez-Montañés; Pedro Paredes; Rosa M. Carro
One of the main concerns of user modelling for adaptive hypermedia deals with automatic user profile acquisition. In this paper we present a new approach to predict sequential/global dimension of Felder-Silverman's learning style model that only makes use of mouse movement patterns. The results obtained in a case study with 18 students are very promising. We found a strong correlation between maximum vertical speed and sequential/global dimension score. Moreover, it was possible to predict whether students' learning styles are global or sequential with high accuracy (94.4%). This suggests that mouse movement patterns can be a powerful source of information about certain user features.
VUMA: A Visual User Modelling Approach for the Personalisation of Adaptive Systems BIBAKFull-Text 341-344
  Melanie B. Späth; Owen Conlan
Current approaches to explicit user modelling are generally time consuming and tedious for the user. Oftentimes poor usability and overly long questionnaires deter the end user from reusing such modelling tools, thus only facilitating explicit personalisation once as they enter the system. This paper proposes a visual approach to user modelling resulting in the VUMA (Visual User Modelling Approach) tool that can be used in a playful and dynamic manner repeatedly during a user's engagement with a personalisation system. This work proposes and evaluates a visually empowering, usable, highly configurable and playful user modelling interface that is utilised to elicit user interests and preferences in a chosen knowledge domain.
Keywords: visual user modelling; user profiling; user interface; personalisation
Bookmark Category Web Page Classification Using Four Indexing and Clustering Approaches BIBAFull-Text 345-348
  Chris Staff
Web browser bookmark files store records of web pages that the user would like to revisit. We use four methods to index and automatically classify documents referred to in 80 bookmark files, based on document title-only and full-text indexing and two clustering approaches. We evaluate the approaches by selecting a bookmark entry to classify from a bookmark file, re-creating a snapshot of the bookmark file to contain only entries created before the selected bookmark entry. The baseline algorithm is 39% accurate at rank 1 when the target category contains 7 entries. By fusing the recommendations of the 4 approaches, we reach 78.7% accuracy on average, recommending at most 3 categories.
Personalization Using Ontologies and Rules BIBAFull-Text 349-352
  Thanh Tran; Haofen Wang; Steffen Lamparter; Philipp Cimiano
Adaptive hypermedia systems can alleviate information overload on the Web by personalising the delivery of resources to the user. These systems are however afflicted with difficulties in the acquisition of user data as well as the general lack of user control on and transparency of the systems' adaptive behavior. In this paper, we argue that the use of rules on top of ontologies can enable adaptive functionality that is both transparent and controllable for users. To this end, we sketch ODAS, a domain ontology for adaptive hypermedia systems, and a model for the specification of adaptation rules.
RSS-Based Interoperability for User Adaptive Systems BIBAFull-Text 353-356
  Yiwen Wang; Federica Cena; Francesca Carmagnola; Omar Cortassa; Cristina Gena
This paper presents an approach to exploit widely used tag annotations to address two important issues in user-adaptive systems: the cold-start problem and the integration of distributed user models. The paper provides an example of re-use of user interaction data (tags) generated by one application into another one in similar domains for providing cross-system recommendations.
Assisting in Reuse of Adaptive Hypermedia Creator's Models BIBAKFull-Text 357-360
  Nadjet Zemirline; Yolaine Bourda; Chantal Reynaud; Fabrice Popineau
The design of Adaptive Hypermedia is a difficult task which can be made easier if generic systems and AH creators' models are reused. We address this design problem in the setting of the GLAM platform only made up of generic components. We present a rule-based approach helping an AH creator in reusing its user and domain models to create a specific adaptive hypermedia. This semi-automatic approach takes the creator's models as specialisations of GLAM generic models and requires the creator to express a minimum set of mappings between his models and the generic ones. The process results in a merged model consisting of the generic and the corresponding specific model. This merged model can be used by the adaptation model.
Keywords: adaptive hypermedia; assisting tools; user and domain modelling

Demo Papers

Convergence of Web and TV Broadcast Data for Adaptive Content Access and Navigation BIBAFull-Text 361-365
  Pieter Bellekens; Kees van der Sluijs; Lora Aroyo; Geert-Jan Houben
iFanzy is a personalized TV guide application aiming at offering users television content in a personalized and context-sensitive way. It consists of a client-server system with multiple clients and devices such that the user can ubiquitously use TV set-top box, mobile phone and Web-based applications to select and receive personalised TV content. TV content and background data from various heterogeneous sources is integrated to provide a transparent knowledge structure, which allows the user to navigate and browse the vast content sets nowadays available. Semantic Web techniques are applied for enriching and aligning Web data and (live) broadcast content. The resulting RDF/OWL knowledge structure is the basis for iFanzy's main functionality, like semantic search of the broadcast content and execution of context-sensitive recommendations.
Recommending Background Information and Related Content in Web 2.0 Portals BIBAFull-Text 366-369
  Andreas Nauerz; Birgitta König-Ries; Martin Welsch
Modern Web 2.0 Portals have become highly collaborative participation platforms. Users do not only retrieve information, they even contribute content. Due to the large number of different users contributing, Web 2.0 sites grow quickly and, most often, in a more uncoordinated way than centrally controlled sites. Finding relevant information can hence become a tedious task. We will demonstrate a solution allowing for the in-place, in-context recommendation of background information with respect to a certain term or topic and for the recommendation of related content being available in the system. Our solution is based on the extraction of enriched units of information which we either gain automatically via unstructured data analysis or by analyzing user-applied annotations. Our main concepts have been embedded and evaluated within IBM's WebSphere Portal.
Adaptive Portals: Context Adaptive Navigation through Large Information Spaces BIBAFull-Text 370-373
  Andreas Nauerz; Martin Welsch; Birgitta König-Ries
Today, Portals provide users with a central point of access to companywide information. Initially they focused on presenting the most valuable and widely used information to users for efficient information access. But the amount of information accessible quickly grew and finding the right information can hence become a tedious task. We will demonstrate a solution for adapting the Portal's structure, especially its navigation and page structures. We allow for advanced adaptations that each user can perform manually as well as for automated adaptations based on user- and context models reflecting users' interests and preferences. Our main concepts have been embedded and evaluated within IBM's WebSphere Portal.
Personalized Recommendations for the Web 3D BIBAFull-Text 374-377
  Bartek Ochab; Nicolas Neubauer; Klaus Obermayer
We introduce the Second Life Location Recommender System (SLLoRS). This system lets users rate and tag locations within the 3D environment Second Life in order to provide personalized recommendations on a collaborative basis. We demonstrate the system as an in-world application and explore some of the general challenges of applying recommendation systems to 3D online environments, like the implementation of data-intensive applications facing restricted computational resources and the segmentation of recommendations in a continuous input space.

Doctoral Consortium

Adaptive User Modelling and Recommendation in Constrained Physical Environments BIBAFull-Text 378-383
  Fabian Bohnert
Visitors to physical educational environments, such as museums, are often overwhelmed by the information available in the space they are exploring. They are confronted with the challenge of finding personally interesting items to view in the available time. Electronic mobile guides can provide guidance and point to relevant information by identifying and recommending items that match a visitor's interests. However, recommendation generation in physical spaces has challenges of its own. Factors such as the spatial layout of the environment and suggested order of item access must be taken into account, as they constrain the recommendation process. This research investigates adaptive user modelling and personalisation approaches that consider such and other constraints.
Learning Style as a Parameter in a Unified e-Learning System Architecture: The Adaptive Diagnosis BIBAKFull-Text 384-388
  Sotirios Botsios; Dimitrios Georgiou
Adaptation and personalization services in e-learning environments are considered the turning point of recent research efforts, as the "one-size-fits-all" approach has some important drawbacks, from the educational point of view. Adaptive Educational Hypermedia Systems in World Wide Web became a very active research field and the need for standardization arose, as the continually augmenting research efforts lacked the interoperability dimension. To this end, we propose an adaptive hypermedia educational system architecture strongly coupled to existing standards that overcomes the above mentioned weakness. Part of such architecture is the development of diagnostic tools capable to recognize certain learner's characteristics to the purpose of providing learning material tailored to the learner's specific needs in an asynchronous learning environment. This paper describes Learning Style diagnosis which can be approached either by the use of probabilistic expert systems or by the use of fuzzy systems.
Keywords: Learning Management Systems; Adaptive Educational Hypermedia Systems; Standards; Learning Style Diagnosis; Probabilistic Expert Systems; Bayesian Networks; Fuzzy Cognitive Maps
Facilitating Collaboration in Virtual Environments BIBAKFull-Text 389-393
  Diana Chihaia
The evolution of learning systems brought improvements to the functionality of their components by offering support and mediating learning, communication and collaboration. However, there are still existing barriers caused by the lack of face to face contact between users. Through our research we aim to provide novel means for supporting the social cohesion of the groups and personalize the e-learning spaces by offering adaptive support in group forming and collaboration processes. As a first step in designing a filtering tool for an adaptive system which recommends application and activities for collaboration within the group, we designed a series of experimental studies on different components of an e-learning system to find out what initiates, influences and increases the level of collaboration between learners.
Keywords: collaboration; adaptive support; team forming
Learner Modelling in Exploratory Learning for Mathematical Generalisation BIBAKFull-Text 394-399
  Mihaela Cocea
Exploratory learning supports creative thinking, allowing learners to control their own learning process, whilst it provides them with help and guidance when necessary. This pedagogical approach emphasises learners' active involvement in authentic activities/tasks that simulate real world processes and has been applied to several domains. In this paper we propose a framework for learner modelling that reflects the incremental nature of knowledge construction as learners are engaged in learning mathematical generalisation. We also describe how such a model can potentially support feedback generation.
Keywords: learner modelling; exploratory learning; feedback generation; mathematical generalisation
GAF: Generic Adaptation Framework BIBAKFull-Text 400-404
  Evgeny Knutov
The Generic Adaptation Framework research project aims to develop a new reference model for the adaptive information systems research field. The new model will extend the well known AHAM reference model, taking into account newly developed techniques and methodologies in this area as well as attempts to capture them in architecture models such as the Munich Reference Model [4], LAOS/LAG [2], [5] and the extension from pure adaptive hypermedia to adaptive information systems, as studied in the Hera research program for instance [6].
Keywords: AHAM; adaptation; generic framework
Engineering Information Systems towards Facilitating Scrutable and Configurable Adaptation BIBAKFull-Text 405-409
  Kevin Koidl; Owen Conlan
End users of Adaptive Hypermedia Systems (AHS) receive an experience that has been tailored towards their specific needs. Several AHS have produced favourable results showing benefits to the user experience [2]. However, the nature of AHS is that they tend to operate across a focused and fixed domain with a single body of content that is known a priori. This approach limits the user's freedom to choose other information sources and restricts the potential impact an adaptive systems may have. To provide more flexibility several service orientated approaches extending traditional AHS architectures have been introduced. This Ph.D. work proposes the re-engineering of information systems in order to support the portability of adaptive services, thus enabling them to personalize any information system on behalf of the user. This approach espouses user empowerment through this mobility and through a highly scrutable and configurable approach to such service-oriented adaptation.
Keywords: Personalization; Adaptation systems and techniques; intelligent agents for personalization and adaptivity
Flexible Adaptivity in AEHS Using Policies BIBAKFull-Text 410-415
  Arne W. Koesling; Daniel Krause; Eelco Herder
In this paper, we show how existing adaptive educational hypermedia systems can be enhanced by policies. In traditional systems, the adaptation is based on predefined user and domain models and fairly restricted adaptation rules. Policies allow for sophisticated and flexible adaptation rules, provided by multiple stakeholders. We present the benefits and feasibility of the approach with AHA! as a hands-on example.
Keywords: AHA; adaptive; hypermedia; trust management; policy
A Validation Framework for Formal Models in Adaptive Work-Integrated Learning BIBAFull-Text 416-420
  Barbara Kump
The focus of my thesis is on the development of a multi-method framework for the validation of formal models (domain model, user model, and teaching model) for adaptive work-integrated learning. In order to test its general applicability, the framework will be applied in four different realistic work domains. In this article, specific challenges of traditional validating approaches in work-integrated learning are being discussed. Eventually, the core ideas and methods of the validation framework are outlined.
A Scrutable User Modelling Infrastructure for Enabling Life-Long User Modelling BIBAFull-Text 421-425
  Demetris Kyriacou
User Modelling is the core component for the majority of personalisation systems. By keeping a model for every user, a system can successfully personalise its content and utilise available resources accordingly. While researching the literature, one can recognize the importance of achieving interoperability across various platforms and systems while attempting to personalise a large diversity of web resources. Furthermore, scrutable solutions allow users to control any modelling process that uses their information. Finally, privacy of user data while exchanging user models from one source to another must be taken in mind. With this paper, a Scrutable User Modelling Infrastructure is presented which blends together these user modelling 1ingredients' and, by adopting Semantic Web technologies, attempts to model a range of life-long user interactions with a variety of web-based systems from the educational, business and social networking domains.
Merging Adaptive Hypermedia and Intelligent Tutoring Systems Using Knowledge Spaces BIBAKFull-Text 426-430
  Amanda Nicholas; Brent Martin
Adaptive Hypermedia and Intelligent Tutoring Systems are both used for computer-based instruction, but their strengths lie in different areas. Adaptive Hypermedia is better suited to the instruction of concepts, while Intelligent Tutoring Systems generally assist in the use of these concepts to solve problems. A general instruction system requires both of these methods of instruction to provide a full learning environment. This paper describes a proposed method of combining Adaptive Hypermedia and Intelligent Tutoring Systems using Knowledge Spaces, a method of mathematically modeling a domain.
Keywords: Intelligent Tutoring Systems; Adaptive Hypermedia; Knowledge Spaces; Constraint-Based Modeling
SemWeB: A Semantic Web Browser for Supporting the Browsing of Users Using Semantic and Adaptive Links BIBAKFull-Text 431-436
  Melike Sah; Wendy Hall; David C. De Roure
Web browsing is a complex activity and in general, users are not guided during browsing. The aim of this research is to support the browsing of users using semantic and adaptive hyperlinks using Semantic Web technologies and personalization methods. In this paper, we propose a novel Semantic Web browser (SemWeB), which uses a behavior-based and an ontology-driven user modeling architecture. In our approach, semantic links and adaptive hypermedia can be achieved on different websites. In addition, user profiles can be easily updated with semantic metadata coming from the Semantic Web browser.
Keywords: Semantic Web Browser; Semantic Web; User Modeling; Ontology; Personalization