[1]
Deep Compositional Cross-modal Learning to Rank via Local-Global Alignment
Session 1: Multimedia Indexing and Search
/
Jiang, Xinyang
/
Wu, Fei
/
Li, Xi
/
Zhao, Zhou
/
Lu, Weiming
/
Tang, Siliang
/
Zhuang, Yueting
Proceedings of the 2015 ACM International Conference on Multimedia
2015-10-26
p.69-78
© Copyright 2015 ACM
Summary: Cross-modal retrieval is a very hot research topic that is imperative to
many applications involving multi-modal data. Discovering an appropriate
representation for multi-modal data and learning a ranking function are
essential to boost the cross-media retrieval. Motivated by the assumption that
a compositional cross-modal semantic representation (pairs of images and text)
is more attractive for cross-modal ranking, this paper exploits the existing
image-text databases to optimize a ranking function for cross-modal retrieval,
called deep compositional cross-modal learning to rank (C2MLR). In this paper,
C2MLR considers learning a multi-modal embedding from the perspective of
optimizing a pairwise ranking problem while enhancing both local alignment and
global alignment. In particular, the local alignment (i.e., the alignment of
visual objects and textual words) and the global alignment (i.e., the
image-level and sentence-level alignment) are collaboratively utilized to learn
the multi-modal embedding common space in a max-margin learning to rank manner.
The experiments demonstrate the superiority of our proposed C2MLR due to its
nature of multi-modal compositional embedding.
[2]
Predicting Continuous Probability Distribution of Image Emotions in
Valence-Arousal Space
Poster Session 1
/
Zhao, Sicheng
/
Yao, Hongxun
/
Jiang, Xiaolei
Proceedings of the 2015 ACM International Conference on Multimedia
2015-10-26
p.879-882
© Copyright 2015 ACM
Summary: Previous works on image emotion analysis mainly focused on assigning a
dominated emotion category or the average dimension values to an image for
affective image classification and regression. However, this is often
insufficient in many applications, as the emotions that are evoked in viewers
by an image are highly subjective and different. In this paper, we propose to
predict the continuous probability distribution of dimensional image emotions
represented in valence-arousal space. By the statistical analysis on the
constructed Image-Emotion-Social-Net dataset, we represent the emotion
distribution as a Gaussian mixture model (GMM), which is estimated by the EM
algorithm. Then we extract commonly used features of different levels for each
image. Finally, we formulize the emotion distribution prediction as a
multi-task shared sparse regression (MTSSR) problem, which is optimized by
iteratively reweighted least squares. Besides, we introduce three baseline
algorithms. Experiments conducted on the Image-Emotion-Social-Net dataset
demonstrate the superiority of the proposed method, as compared to some
state-of-the-art approaches.
[3]
Differentially Private Histogram Publication for Dynamic Datasets: an
Adaptive Sampling Approach
Session 5C: Privacy
/
Li, Haoran
/
Xiong, Li
/
Jiang, Xiaoqian
/
Liu, Jinfei
Proceedings of the 2015 ACM Conference on Information and Knowledge
Management
2015-10-19
p.1001-1010
© Copyright 2015 ACM
Summary: Differential privacy has recently become a de facto standard for private
statistical data release. Many algorithms have been proposed to generate
differentially private histograms or synthetic data. However, most of them
focus on "one-time" release of a static dataset and do not adequately address
the increasing need of releasing series of dynamic datasets in real time. A
straightforward application of existing histogram methods on each snapshot of
such dynamic datasets will incur high accumulated error due to the
composibility of differential privacy and correlations or overlapping users
between the snapshots. In this paper, we address the problem of releasing
series of dynamic datasets in real time with differential privacy, using a
novel adaptive distance-based sampling approach. Our first method, DSFT, uses a
fixed distance threshold and releases a differentially private histogram only
when the current snapshot is sufficiently different from the previous one,
i.e., with a distance greater than a predefined threshold. Our second method,
DSAT, further improves DSFT and uses a dynamic threshold adaptively adjusted by
a feedback control mechanism to capture the data dynamics. Extensive
experiments on real and synthetic datasets demonstrate that our approach
achieves better utility than baseline methods and existing state-of-the-art
methods.
[4]
Designing a Social Mobile Platform for Diabetes Self-management: A
Theory-Driven Perspective
Designing Social Media
/
Nguyen, Hoang D.
/
Jiang, Xinyi
/
Poo, Danny Chiang Choon
SCSM 2015: 7th International Conference on Social Computing and Social Media
2015-08-02
p.67-77
Keywords: Diabetes mellitus; Self-management; mHealth; Social support; Social presence
© Copyright 2015 Springer International Publishing Switzerland
Summary: Diabetes mellitus (DM) is increasingly being accepted as a lifelong public
health problem with profound consequences on the worldwide healthcare system.
Self-management, therefore, has been long suggested as an integral solution of
diabetes treatment [1] which requires patients to adopt strained lifestyle
modifications (e.g., balancing diets and frequent monitoring of blood glucose)
[2, 3]. With the proliferation of smart devices, this study proposes a
theoretical framework as an important guideline for designing and prototyping a
life-changing mobile platform for a next-generation diabetes self-management.
It revolutionises the interaction between patients and their smart phone with a
high degree of media richness and social connectivity for better health
management success.
[5]
Exploring Principles-of-Art Features For Image Emotion Recognition
Multimedia Art and Entertainment
/
Zhao, Sicheng
/
Gao, Yue
/
Jiang, Xiaolei
/
Yao, Hongxun
/
Chua, Tat-Seng
/
Sun, Xiaoshuai
Proceedings of the 2014 ACM International Conference on Multimedia
2014-11-03
p.47-56
© Copyright 2014 ACM
Summary: Emotions can be evoked in humans by images. Most previous works on image
emotion analysis mainly used the elements-of-art-based low-level visual
features. However, these features are vulnerable and not invariant to the
different arrangements of elements. In this paper, we investigate the concept
of principles-of-art and its influence on image emotions.
Principles-of-art-based emotion features (PAEF) are extracted to classify and
score image emotions for understanding the relationship between artistic
principles and emotions. PAEF are the unified combination of representation
features derived from different principles, including balance, emphasis,
harmony, variety, gradation, and movement. Experiments on the International
Affective Picture System (IAPS), a set of artistic photography and a set of
peer rated abstract paintings, demonstrate the superiority of PAEF for
affective image classification and regression (with about 5% improvement on
classification accuracy and 0.2 decrease in mean squared error), as compared to
the state-of-the-art approaches. We then utilize PAEF to analyze the emotions
of master paintings, with promising results.
[6]
Decoding Auditory Saliency from FMRI Brain Imaging
Posters 1
/
Zhao, Shijie
/
Jiang, Xi
/
Han, Junwei
/
Hu, Xintao
/
Zhu, Dajiang
/
Lv, Jinglei
/
Zhang, Tuo
/
Guo, Lei
/
Liu, Tianming
Proceedings of the 2014 ACM International Conference on Multimedia
2014-11-03
p.873-876
© Copyright 2014 ACM
Summary: Given the growing number of available audio streams through a variety of
sources and distribution channels, effective and advanced computational audio
analysis has received increasing interest in the multimedia field. However, the
effectiveness of current audio analysis strategies might be hampered due to the
lack of effective representation of high-level semantics perceived by the human
and the lack of effective approaches to bridging the gaps between most
low-level acoustic features and high-level semantic features. This semantic gap
has become the 'bottleneck' problem in audio analysis. In this paper, we
propose a computational framework to decode biologically-plausible auditory
saliency using high-level features derived from functional magnetic resonance
imaging (fMRI) which monitors the human brain's response under the natural
stimulus of audio listening. Specifically, we identify meaningful intrinsic
brain networks which are involved in audio listening via effective online
dictionary learning and sparse representation of whole-brain fMRI signals,
reconstruct auditory saliency features using those identified brain network
components, and perform group-wise analysis to identify consistent 'brain
decoders' of the saliency features across different excerpts and participants.
Experimental results demonstrate that the auditory saliency features are
effectively decoded via our methods, which potentially provide opportunities
for various applications in the multimedia field.
[7]
Ranking Optimization with Constraints
IR Session 9: Machine Learning
/
Wu, Fangzhao
/
Xu, Jun
/
Li, Hang
/
Jiang, Xin
Proceedings of the 2014 ACM Conference on Information and Knowledge
Management
2014-11-03
p.1049-1058
© Copyright 2014 ACM
Summary: This paper addresses the problem of post-processing of ranking in search,
referred to as post ranking. Although important, no research seems to have been
conducted on the problem, particularly with a principled approach, and in
practice ad-hoc ways of performing the task are being adopted. This paper
formalizes the problem as constrained optimization in which the constraints
represent the post-processing rules and the objective function represents the
trade-off between adherence to the original ranking and satisfaction of the
rules. The optimization amounts to refining the original ranking result based
on the rules. We further propose a specific probabilistic implementation of the
general formalization on the basis of the Bradley-Terry model, which is
theoretically sound, effective, and efficient. Our experimental results, using
benchmark datasets and enterprise search dataset, show that the proposed method
works much better than several baseline methods of utilizing rules.
[8]
ContextSense: unobtrusive discovery of incremental social context using
dynamic bluetooth data
Posters
/
Chen, Zhenyu
/
Chen, Yiqiang
/
Hu, Lisha
/
Wang, Shuangquan
/
Jiang, Xinlong
/
Ma, Xiaojuan
/
Lane, Nicholas D.
/
Campbell, Andrew T.
Adjunct Proceedings of the 2014 International Joint Conference on Pervasive
and Ubiquitous Computing
2014-09-13
v.2
p.23-26
© Copyright 2014 ACM
Summary: User-centric ambient social contexts can be effectively captured by dynamic
bluetooth data. However, conventional approaches for training classifiers
struggle with social contexts that are incrementally constructed and
continuously discovered in everyday environments. Incremental social contexts
can confuse a classifier because it assumes that the number and composition of
context classes is fixed throughout training and inference phases. To address
this challenge we propose ContextSense, an ELM-based learning method for
continuous and unobtrusive discovery of new social contexts incrementally from
dynamic bluetooth data. Experimental results show that ContextSense can
automatically cope with "incremental social context" classes that appear
unpredictably in the real-world.
[9]
SAP dissimilarity based high performance Wi-Fi indoor localization
Posters
/
Gu, Yang
/
Chen, Yiqiang
/
Liu, Junfa
/
Jiang, Xinlong
Adjunct Proceedings of the 2014 International Joint Conference on Pervasive
and Ubiquitous Computing
2014-09-13
v.2
p.55-58
© Copyright 2014 ACM
Summary: There are two longstanding issues: the fluctuation of wireless signal and
the unstability of Access Point (AP), which greatly affect the performance of
Wi-Fi based indoor localization. Most existing fingerprint based Wi-Fi
localization methods adopt machine learning or data mining algorithms to get
the location information; however, they ignore some intrinsic factors.
According to massive observations, we discover some underlying characteristics
of Wi-Fi indoor localization from the view of signal strength and AP. Hence, a
new dissimilarity based localization method SAP (Signal-AP) is proposed to
implement high performance indoor localization. The results show that SAP not
only improves the localization accuracy, but also has desirable scalability of
environment.
[10]
Pupil responses during discrete goal-directed movements
The eyes have it
/
Jiang, Xianta
/
Atkins, M. Stella
/
Tien, Geoffrey
/
Bednarik, Roman
/
Zheng, Bin
Proceedings of ACM CHI 2014 Conference on Human Factors in Computing Systems
2014-04-26
v.1
p.2075-2084
© Copyright 2014 ACM
Summary: Pupil size is known to correlate with the changes of cognitive task
workloads, but how the pupil responds to requirements of basic goal-directed
motor tasks involved in human-machine interactions is not yet clear. This work
conducted a user study to investigate the pupil dilations during aiming in a
tele-operation setting, with the purpose of better understanding how the
changes in task requirements are reflected by the changes of pupil size. The
task requirements, managed by Fitts' index of difficulty (ID), i.e. the size
and distance apart of the targets, were varied between tasks, and pupil
responses to different task IDs were recorded. The results showed that pupil
diameter can be employed as an indicator of task requirements in goal-directed
movements-higher task difficulty evoked higher valley to peak pupil dilation,
and the peak pupil dilation occurred after a longer delay. These findings
contribute to the foundation for developing methods to objectively evaluate
interactive task requirements using pupil parameters during goal-directed
movements in HCI.
[11]
Pupil dilations during target-pointing respect Fitts' law
Visual attention and eye movements
/
Jiang, Xianta
/
Atkins, M. Stella
/
Tien, Geoffrey
/
Zheng, Bin
/
Bednarik, Roman
Proceedings of the 2014 Symposium on Eye Tracking Research &
Applications
2014-03-26
p.175-182
© Copyright 2014 ACM
Summary: Pupil size is known to correlate with changes of cognitive task workloads,
but the pupillary response to requirements of basic goal-directed motor tasks
is not yet clear, although pointing with tools is a ubiquitous human task. This
work describes a user study to investigate the pupil dilations during aiming in
two tele-operation tasks with different target settings, one aiming at targets
with different sizes located at constant distance apart, and the other aiming
at targets varying in different distances. The task requirements in each task
were defined by Fitts' index of difficulty (ID). The purpose of this work is to
further explore how the changes in task requirements are reflected by the
changes of pupil size, i.e., whether the pupil responds to either target size
or target distance, or to both of them. Pupil responses to different task IDs
were recorded in each task. The results showed that the pupil responds to the
changes of ID, not just to the change of target size. This implies that pupil
diameter can be employed as an indicator of task requirement in goal-directed
movements, because higher task difficulty evoked higher peak pupil dilation
which occurred with longer delay. These findings can be used for detailed
understanding of eye-hand coordination mechanisms in interactive systems and
contribute to the foundation for developing methods to objectively evaluate
interactive task requirements using pupil parameters during goal-directed
movements.
[12]
Verbal gaze instruction matches visual gaze guidance in laparoscopic skills
training
Poster abstracts
/
Tien, Geoffrey
/
Atkins, M. Stella
/
Jiang, Xianta
/
Zheng, Bin
/
Bednarik, Roman
Proceedings of the 2014 Symposium on Eye Tracking Research &
Applications
2014-03-26
p.331-334
© Copyright 2014 ACM
Summary: Novices were trained to perform a unimanual peg transport task in a
laparoscopic training box with an illuminated interior displayed on a monitor.
Subjects were divided into two groups; one group was verbally instructed to
direct their gaze at distant targets, while the other group had their gaze
behaviour implicitly manipulated using distant target illumination. Both groups
achieved similar task completion times post-training and developed peripheral
vision strategies leading to delayed foveation on targets until the instrument
was closer to its destination, although the ability to focus on targets earlier
during manual movements as done by an expert surgeon was quickly regained by
the verbal instruction group post-training. This suggests that care should be
taken when employing visual attention cuing methods such as target highlighting
for training eye-hand coordination skills, as simple verbal instruction may be
sufficient to help trainees to adopt more expert-like gaze behaviours.
[13]
Introducing Human Performance Modeling in Digital Nuclear Power Industry
Cultural Issues in Business and Industry
/
Jiang, Xiang
/
Gao, Qin
/
Li, Zhizhong
CCD 2013: 5th International Conference on Cross-Cultural Design, Part II:
Cultural Differences in Everyday Life
2013-07-21
v.2
p.27-36
Keywords: Digitalization; Nuclear power plants; Performance influence factors; Human
performance modeling
© Copyright 2013 Springer-Verlag
Summary: Human performance modeling (HPM) can be used to explain and predict human
behaviors under certain situations, helping designers in the design stage
through evaluating the interface, procedure, staffing, etc. This study
discusses the feasibility of introducing HPM methods into digital nuclear power
industry through 1) the new characteristics of human-system interaction/human
performance in digital main control rooms (MCRs) of nuclear power plants
(NPPs), 2) the simulating abilities of available HPMs on their latest progress.
Based on the review of the two issues, we conclude that: 1) digitalization of
NPPs changes operators' performance through the system, task, environment and
human himself. 2) HPM is classified as human reliability modeling and cognitive
modeling. The lack of performance data could be an obstacle for applying human
reliability modeling in digital MCRs. The unclear underlying mechanism of
human-system interaction in digital MCRs constrains the introducing of
cognitive modeling.
[14]
Towards an effective and unbiased ranking of scientific literature through
mutual reinforcement
IR track: digital libraries and citation analysis
/
Jiang, Xiaorui
/
Sun, Xiaoping
/
Zhuge, Hai
Proceedings of the 2012 ACM Conference on Information and Knowledge
Management
2012-10-29
p.714-723
© Copyright 2012 ACM
Summary: It is important to help researchers find valuable scientific papers from a
large literature collection containing information of authors, papers and
venues. Graph-based algorithms have been proposed to rank papers based on
networks formed by citation and co-author relationships. This paper proposes a
new graph-based ranking framework MutualRank that integrates mutual
reinforcement relationships among networks of papers, researchers and venues to
achieve a more synthetic, accurate and fair ranking result than previous
graph-based methods. MutualRank leverages the network structure information
among papers, authors, and their venues available from a literature collection
dataset and sets up a unified mutual reinforcement model that involves both
intra- and inter-network information for ranking papers, authors and venues
simultaneously. To evaluate, we collect a set of recommended papers from
websites of graduate-level computational linguistics courses of 15 top
universities as the benchmark and apply different methods to estimate paper
importance. The results show that MutualRank greatly outperforms the
competitors including Pag-eRank, HITS and CoRank in ranking papers as well as
researchers. The experimental results also demonstrate that venues ranked by
MutualRank are reasonable.
[15]
Saccadic delays on targets while watching videos
Uses and applications
/
Atkins, M. Stella
/
Jiang, Xianta
/
Tien, Geoffrey
/
Zheng, Bin
Proceedings of the 2012 Symposium on Eye Tracking Research &
Applications
2012-03-28
p.405-408
© Copyright 2012 ACM
Summary: To observe whether there is a difference in eye gaze between doing a task,
and watching a video of the task, we recorded the gaze of 17 subjects
performing a simple surgical eye-hand coordination task. We also recorded eye
gaze of the same subjects later while they were watching videos of their
performance.
We divided the task into 9 or more sub-tasks, each of which involved a large
hand movement to a new target location. We analyzed the videos manually and
located the video frame for each sub-task where the operator's saccadic
movement began, and the frame where the watcher's eye movement began. We found
a consistent delay of about 600 ms between initial eye movement when doing the
task, and initial eye movement when watching the task, observed in 96.3% of the
sub-tasks.
For the first time, we have quantified the differences between doing and
watching a manual task. This will help develop gaze-based training strategies
for manual tasks.
[16]
Tulsa: web search for writing assistance
Demonstrations
/
Ding, Duo
/
Jiang, Xingping
/
Scott, Matthew R.
/
Zhou, Ming
/
Yu, Yong
Proceedings of the 34th Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2011-07-25
p.1287-1288
© Copyright 2011 ACM
[17]
Query expansion based on a semantic graph model
Doctoral consortium
/
Jiang, Xue
Proceedings of the 34th Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2011-07-25
p.1315-1316
© Copyright 2011 ACM
Summary: Query expansion is a classical topic in the field of information retrieval,
which is proposed to bridge the gap between searchers' information intents and
their queries. Previous researches usually expand queries based on document
collections, or some external resources such as WordNet and Wikipedia [1, 2, 3,
4, 5]. However, it seems that independently using one of these resources has
some defects, document collections lack semantic information of words, while
WordNet and Wikipedia may not include domain-specific knowledge in certain
document collection. Our work aims to combine these two kinds of resources to
establish an expansion model which represents not only domain-specific
information but also semantic information. In our preliminary experiments, we
construct a two-layer word graph and use Random-Walk algorithm to calculate the
weights of each term in pseudo-relevance feedback documents, then select the
highest weighted term to expand original query. The first layer of the word
graph contains terms in related documents, while the second layer contains
semantic senses corresponding to these terms. These terms and semantic senses
are treated as vertices of the graph and connected with each other by all
possible relationships, such as mutual information and semantic similarities.
We utilized mutual information, semantic similarity and uniform distribution as
the weight of term-term relation, sense-sense relation and word-sense relation
respectively. Though these experiments show that our expansion outperform
original queries, we are troubled with some difficult problems.
Given the framework of semantic graph model, we need more effort to find out
an optimal graph to represent the relationships between terms and their
semantic senses. We utilized a two-layer graph model in our preliminary
research, where terms from different documents are treated equally. Maybe we
can introduce the document as a third layer in future work, where we can differ
the same terms in different documents according to document relevance and
context.
Then we need appropriately represent initial weights of this words, senses
and relationships. Various measures for weights of terms and term relations
have been proved effective in other information retrieval tasks, such as TFIDF,
mutual information (MI), but there is little research on weights for semantic
senses and their relations. For polysemous words, we add all of their semantic
senses to the graph and assume that these senses are uniformly distributed.
Actually, it is not precise for a word in a special document and query. As we
know, a polysemous word may have only one or two senses in a document, and they
are not uniformly distributed. Give a word, what we should do is to determine
its word senses in a relevant document and estimate the distribution of these
senses. Word sense disambiguation may help us in this problem. Then, there are
many methods to compute word similarity according to WordNet, which we use to
represent the weights of relationships between word senses. Varelas et al
implemented some popular methods to compute semantic similarity by mapping
terms to an ontology and examining their relationships in that ontology [4]. We
also need to know which algorithm for semantic similarity is most suitable for
our model.
Additional, WordNet is suitable to calculate word similarity but not
suitable to measure word relevance. The inner hyperlinks of Wikipedia could
help us to calculate word relevance. We wish to find an effective way to
combine the similarity measure from WordNet and relevance measure from
Wikipedia, which may completely reflect word relationships.
[18]
A comparison of how users search on web finding and re-finding tasks
Search
/
Pu, Hsiao-Tieh
/
Jiang, Xin-Yu
Proceedings of the 2011 iConference
2011-02-08
p.446-451
© Copyright 2011 ACM
Summary: This study is to investigate how users search for web information for the
first time (information finding) and locate previously found results on a
subsequent effort (information re-finding). It constructs a two-staged
experiment and employs various methods to compare users' search performance on
different types of search tasks. The preliminary results show that participants
in the study produced more interactions with search tools in the re-finding
stage. Though the participants spent less time in the re-finding than that in
the finding stage, the difference was not significant. It is worth noting that
in some cases the search performance of re-finding was even lower than that of
finding. This reveals that re-finding may not work effectively for all search
tasks. Further research is needed to investigate on what circumstances users
had better initiate new searches rather than repeat previous searches in the
re-finding stage.
[19]
Human-centered attention models for video summarization
Human-centered HCI
/
Li, Kaiming
/
Guo, Lei
/
Faraco, Carlos
/
Zhu, Dajiang
/
Deng, Fan
/
Zhang, Tuo
/
Jiang, Xi
/
Zhang, Degang
/
Chen, Hanbo
/
Hu, Xintao
/
Miller, Stephen
/
Liu, Tianming
Proceedings of the 2010 International Conference on Multimodal Interfaces
2010-11-08
p.27
© Copyright 2010 ACM
Summary: A variety of user attention models for video/audio streams have been
developed for video summarization and abstraction, in order to facilitate
efficient video browsing and indexing. Essentially, human brain is the end user
and evaluator of multimedia content and representation, and its responses can
provide meaningful guidelines for multimedia stream summarization. For example,
video/audio segments that significantly activate the visual, auditory, language
and working memory systems of the human brain should be considered more
important than others. It should be noted that user experience studies could be
useful for such evaluations, but are suboptimal in terms of their capability of
accurately capturing the full-length dynamics and interactions of the brain's
response. This paper presents our preliminary efforts in applying the brain
imaging technique of functional magnetic resonance imaging (fMRI) to quantify
and model the dynamics and interactions between multimedia streams and brain
response, when the human subjects are presented with the multimedia clips, in
order to develop human-centered attention models that can be used to guide and
facilitate more effective and efficient multimedia summarization. Our initial
results are encouraging.
[20]
Fast top-k simple shortest paths discovery in graphs
DB track: top-K and shortest path processing
/
Gao, Jun
/
Qiu, Huida
/
Jiang, Xiao
/
Wang, Tengjiao
/
Yang, Dongqing
Proceedings of the 2010 ACM Conference on Information and Knowledge
Management
2010-10-26
p.509-518
© Copyright 2010 ACM
Summary: With the wide applications of large scale graph data such as social
networks, the problem of finding the top-k shortest paths attracts increasing
attention. This paper focuses on the discovery of the top-k simple shortest
paths (paths without loops). The well known algorithm for this problem is due
to Yen, and the provided worst-case bound O(kn(m + nlogn)), which comes from
O(n) times single-source shortest path discovery for each of k shortest paths,
remains unbeaten for 30 years, where n is the number of nodes and m is the
number of edges. In this paper, we observe that there are shared sub-paths
among O(kn) single-source shortest paths. The basic idea behind our method is
to pre-compute the shortest paths to the target node, and utilize them to
reduce the discovery cost at running time. Specifically, we transform the
original graph by encoding the pre-computed paths, and prove that the shortest
path discovered over the transformed graph is equivalent to that in the
original graph. Most importantly, the path discovery over the transformed graph
can be terminated much earlier than before. In addition, two optimization
strategies are presented. One is to reduce the total iteration times for
shortest path discovery, and the other is to prune the search space in each
iteration with an adaptively-determined threshold. Although the worst-case
complexity cannot be lowered, our method is proven to be much more efficient in
a general case. The final extensive experimental results (on both real and
synthetic graphs) also show that our method offers a significant performance
improvement over the existing ones.
[21]
TC-DCA: a system for text classification based on document's content
allocation
Demo session 1: IR
/
Li, Wenbo
/
Sun, Le
/
Zhang, Zhenzhong
/
Jiang, Xue
/
Zhang, Weiru
Proceedings of the 2010 ACM Conference on Information and Knowledge
Management
2010-10-26
p.1937-1938
© Copyright 2010 ACM
Summary: The text classification methods heavily depend on machine learning
algorithms with abstract mathematic metrics, which obstruct the direct
observation and intuitive understanding of the text-specific classification. In
this paper, we model a document as a Document-Classes-Topics top-down
hierarchical structure. Furthermore, by running the document generation
procedure, we can obtain each class's content share, which not only can be used
to make the classification decision but also can provide a natural
visualization approach for text classification. We implement this idea by a new
tool named TC-DCA, which provides the visualization of text classification
result, where the target document is expressed graphically as its content's
allocation on every class. TC-DCA can also perform the drilling down operation
to reveal the classification effect of each word of the document.
[22]
A ranking approach to keyphrase extraction
Posters
/
Jiang, Xin
/
Hu, Yunhua
/
Li, Hang
Proceedings of the 32nd Annual International ACM SIGIR Conference on
Research and Development in Information Retrieval
2009-07-19
p.756-757
Keywords: keyphrase extraction, learning to rank, ranking SVM
© Copyright 2009 ACM
Summary: This paper addresses the issue of automatically extracting keyphrases from a
document. Previously, this problem was formalized as classification and
learning methods for classification were utilized. This paper points out that
it is more essential to cast the problem as ranking and employ a learning to
rank method to perform the task. Specifically, it employs Ranking SVM, a
state-of-art method of learning to rank, in keyphrase extraction. Experimental
results on three datasets show that Ranking SVM significantly outperforms the
baseline methods of SVM and Naive Bayes, indicating that it is better to
exploit learning to rank techniques in keyphrase extraction.
[23]
Evaluation of an Adaptive Interface for Fault Management
COGNITIVE ENGINEERING AND DECISION MAKING: CE9 - Information Display and
Cognitive Artifacts
/
Letsu-Dake, Emmanuel
/
Ntuen, Celestine A.
/
Seong, Younho
/
Jiang, Xiaochun (Steve)
Proceedings of the Human Factors and Ergonomics Society 52nd Annual Meeting
2008-09-22
v.52
p.373-377
© Copyright 2008 HFES
Summary: Adaptive interfaces support the performance of human operators by providing
the appropriate aid, information or functionality at any point in operation.
This study presents an experimental evaluation of an adaptive interface.
Comparing an adaptive interface to a non-adaptive one for the same process
through experimentation can reveal its relative weaknesses and strengths. A
sample simulation environment that controls a thermal-hydraulic process is used
for this study. Using four performance criteria, the adaptive interface
performed significantly better than the non-adaptive one.
[24]
Information retrieval and knowledge discovery on the semantic web of
traditional Chinese medicine
Posters
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Wu, Zhaohui
/
Yu, Tong
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Chen, Huajun
/
Jiang, Xiaohong
/
Feng, Yi
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Mao, Yuxin
/
Wang, Heng
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Tang, Jingming
/
Zhou, Chunying
Proceedings of the 2008 International Conference on the World Wide Web
2008-04-21
p.1085-1086
Keywords: information retrieval, knowledge discovery, semantic web
© Copyright 2008 International World Wide Web Conference Committee (IW3C2)
Summary: We conduct the first systematical adoption of the Semantic Web solution in
the integration, management, and utilization of TCM information and knowledge
resources. As the results, the largest TCM Semantic Web ontology is engineered
as the uniform knowledge representation mechanism; the ontology-based query and
search engine is deployed, mapping legacy and heterogeneous relational
databases to the Semantic Web layer for query and search across database
boundaries; the first global herb-drug interaction network is mapped through
semantic integration, and the semantic graph mining methodology is implemented
for discovering and interpreting interesting patterns from this network. The
platform and underlying methodology are proved effective in TCM-related drug
usage, discovery, and safety analysis.
[25]
Building high performance DVR via HLA, scene graph and parallel rendering
Rendering
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Xiong, Hua
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Wang, Zonghui
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Jiang, Xiaohong
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Shi, Jiaoying
Proceedings of the 2007 ACM Symposium on Virtual Reality Software and
Technology
2007-11-05
p.141-144
Keywords: collaborative environments, distributed simulation, distributed virtual
reality, graphics cluster, high level architecture, parallel rendering, scene
graph
© Copyright 2007 ACM
Summary: Distributed simulation and parallel rendering based on PC cluster have seen
great success in recent years. To improve the overall performance, there is a
trend to integrate modeling, simulation and visualization into a common
distributed environment. In this paper, we propose a unified framework of
building high performance distributed virtual reality (DVR) applications. The
core components of this framework include the High Level Architecture (HLA),
scene graphs and parallel rendering. The HLA supports interactive distributed
simulation. Scene graphs are efficient to organize and manipulate scene data.
And parallel rendering provides powerful rendering ability. This paper presents
the in-depth architectural analysis of each components and derives a design
that integrates them into a unified framework. Two DVR applications, including
a remote navigation of massive virtual scenes and a multi-player video game,
have been developed to evaluate the framework performance.
