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Articles 5761 - 5790 of 7256
Full-Text Articles in Computer Sciences
Multi-Order Neurons For Evolutionary Higher Order Clustering And Growth, Kiruthika Ramanathan, Sheng Uei Guan
Multi-Order Neurons For Evolutionary Higher Order Clustering And Growth, Kiruthika Ramanathan, Sheng Uei Guan
Research Collection School Of Computing and Information Systems
This letter proposes to use multiorder neurons for clustering irregularly shaped data arrangements. Multiorder neurons are an evolutionary extension of the use of higher-order neurons in clustering. Higher-order neurons parametrically model complex neuron shapes by replacing the classic synaptic weight by higher-order tensors. The multiorder neuron goes one step further and eliminates two problems associated with higher-order neurons. First, it uses evolutionary algorithms to select the best neuron order for a given problem. Second, it obtains more information about the underlying data distribution by identifying the correct order for a given cluster of patterns. Empirically we observed that when the …
Preventing Location-Based Identity Inference In Anonymous Spatial Queries, Panos Kalnis, Gabriel Ghinita, Kyriakos Mouratidis, Dimitris Papadias
Preventing Location-Based Identity Inference In Anonymous Spatial Queries, Panos Kalnis, Gabriel Ghinita, Kyriakos Mouratidis, Dimitris Papadias
Research Collection School Of Computing and Information Systems
The increasing trend of embedding positioning capabilities (for example, GPS) in mobile devices facilitates the widespread use of location-based services. For such applications to succeed, privacy and confidentiality are essential. Existing privacy-enhancing techniques rely on encryption to safeguard communication channels, and on pseudonyms to protect user identities. Nevertheless, the query contents may disclose the physical location of the user. In this paper, we present a framework for preventing location-based identity inference of users who issue spatial queries to location-based services. We propose transformations based on the well-established K-anonymity concept to compute exact answers for range and nearest neighbor search, without …
Towards Tractable Local Closed World Reasoning For The Semantic Web, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler
Towards Tractable Local Closed World Reasoning For The Semantic Web, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Recently, the logics of minimal knowledge and negation as failure MKNF [12] was used to introduce hybrid MKNF knowledge bases [14], a powerful formalism for combining open and closed world reasoning for the Semantic Web. We present an extension based on a new three-valued framework including an alternating fixpoint, the well-founded MKNF model. This approach, the well-founded MKNF semantics, derives its name from the very close relation to the corresponding semantics known from logic programming. We show that the well-founded MKNF model is the least model among all (three-valued) MKNF models, thus soundly approximating also the two-valued MKNF models from …
Semantic Web For Health Care And Biomedical Informatics, Amit P. Sheth
Semantic Web For Health Care And Biomedical Informatics, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Rss Management: An Rss Reader To Manage Rss Feeds That Efficiently And Effectively Pulls And Filters Feeds With Minimal Bandwidth Consumption, Brian Cooper
Theses and Dissertations
In the early 2000s, RSS (Really Simple Syndication) was launched into cyber space and rapidly gained fame by existing as the underlying technology that fueled millions of web logs (blogs). Soon RSS feeds appeared for news, multimedia podcasting, and many other types of information on the Internet. RSS introduced a new way to syndicate information that allowed anyone interested to subscribe to published content and pull the information to an aggregator, (RSS reader application), at their discretion. RSS made it simple for people to keep up with online content without having to continuously check websites for new content. This new …
Understanding Highly Competent Information System Users, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Understanding Highly Competent Information System Users, Brenda Eschenbrenner, Fiona Fui-Hoon Nah
Research Collection School Of Computing and Information Systems
Individuals differ in their abilities to use information systems (IS) effectively, with some achieving exceptional performance in IS use. Using the Repertory Grid Technique, this research identifies attributes of highly competent IS users that distinguish them from less competent users. Using the Grounded Theory approach, we identified categories and sub-categories of these attributes and used them to develop a conceptual framework to explain IS User Competency. The findings indicate that highly competent users differ from less competent users in their Personality Traits and Disposition Factors, General Cognitive Abilities, Social Skills and Tendencies, Experiential Learning Factors, Domain Knowledge of and Skills …
Leveraging Semantic Web Techniques To Gain Situational Awareness, Amit P. Sheth
Leveraging Semantic Web Techniques To Gain Situational Awareness, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
The Librarian As Hacker, Getting More From Google, R Philip Reynolds
The Librarian As Hacker, Getting More From Google, R Philip Reynolds
Librarian and Staff Publications
This paper will cover four areas. First it will discuss the research habits of search engine users and some of the problems with these habits. Then it will discuss librarians' use of search engines. Here we encounter the real question: Do we do much better? Can we use a search engines to their full potential? When needed, can we hack an engine to make it perform beyond its intended function? Can we use a clever workaround to solve a problem? Or are we on a level playing field with our patrons once we get outside traditional database searching? Google currently …
Conjunctive Queries For A Tractable Fragment Of Owl 1.1, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Conjunctive Queries For A Tractable Fragment Of Owl 1.1, Markus Krotzsch, Sebastian Rudolph, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Despite the success of the Web Ontology Language OWL, the development of expressive means for querying OWL knowledge bases is still an open issue. In this paper, we investigate how a very natural and desirable form of queries-namely conjunctive ones-can be used in conjunction with OWL such that one of the major design criteria of the latter-namely decidability-can be retained. More precisely, we show that querying the tractable fragment EL++ of OWL 1.1 is decidable. We also provide a complexity analysis and show that querying unrestricted EL++ is undecidable.
Can Semantic Web Techniques Empower Comprehension And Projection In Cyber Situational Awareness?, Amit P. Sheth
Can Semantic Web Techniques Empower Comprehension And Projection In Cyber Situational Awareness?, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Semantic Convergence Of Wikipedia Articles, Christopher J. Thomas, Amit P. Sheth
Semantic Convergence Of Wikipedia Articles, Christopher J. Thomas, Amit P. Sheth
Kno.e.sis Publications
Social networking, distributed problem solving and human computation have gained high visibility. Wikipedia is a well established service that incorporates aspects of these three fields of research. For this reason it is a good object of study for determining quality of solutions in a social setting that is open, completely distributed, bottom up and not peer reviewed by certified experts. In particular, this paper aims at identifying semantic convergence of Wikipedia articles; the notion that the content of an article stays stable regardless of continuing edits. This could lead to an automatic recommendation of good article tags but also add …
Supporting Complex Thematic, Spatial And Temporal Queries Over Semantic Web Data, Matthew Perry, Amit P. Sheth, Farshad Hakimpour, Prateek Jain
Supporting Complex Thematic, Spatial And Temporal Queries Over Semantic Web Data, Matthew Perry, Amit P. Sheth, Farshad Hakimpour, Prateek Jain
Kno.e.sis Publications
Spatial and temporal data are critical components in many applications. This is especially true in analytical domains such as national security and criminal investigation. Often, the analytical process requires uncovering and analyzing complex thematic relationships between disparate people, places and events. Fundamentally new query operators based on the graph structure of Semantic Web data models, such as semantic associations, are proving useful for this purpose. However, these analysis mechanisms are primarily intended for thematic relationships. In this paper, we describe a framework built around the RDF metadata model for analysis of thematic, spatial and temporal relationships between named entities. We …
Experimenting Vireo-374: Bag-Of-Visual-Words And Visual-Based Ontology For Semantic Video Indexing And Search, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Feng Wang, Wanlei Zhao, Hung-Khoon Tan, Xiao Wu
Experimenting Vireo-374: Bag-Of-Visual-Words And Visual-Based Ontology For Semantic Video Indexing And Search, Chong-Wah Ngo, Yu-Gang Jiang, Xiaoyong Wei, Feng Wang, Wanlei Zhao, Hung-Khoon Tan, Xiao Wu
Research Collection School Of Computing and Information Systems
In this paper, we present our approaches and results of high-level feature extraction and automatic video search in TRECVID-2007.
Sloque: Slot-Based Query Expansion For Complex Questions, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Sloque: Slot-Based Query Expansion For Complex Questions, Maggy Anastasia Suryanto, Ee Peng Lim, Aixin Sun, Roger Hsiang-Li Chiang
Research Collection School Of Computing and Information Systems
Searching answers to complex questions is a challenging IR task. In this paper, we examine the use of query templates with semantic slots to formulate slot-based queries. These queries have query terms assigned to entity and relationship slots. We develop several query expansion methods for slot-based queries so as to improve their retrieval effectiveness on a document collection. Each method consists of a combination of term scoring scheme, term scoring formula, and term assignment scheme. Our preliminary experiments evaluate these different slot-based query expansion methods on a collection of news documents,and conclude that:(1) slot-based queries yield better retrieval accuracy compared …
On Improving Wikipedia Search Using Article Quality, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady Wirawan Lauw, Ba-Quy Vuong
On Improving Wikipedia Search Using Article Quality, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady Wirawan Lauw, Ba-Quy Vuong
Research Collection School Of Computing and Information Systems
Wikipedia is presently the largest free-and-open online encyclopedia collaboratively edited and maintained by volunteers. While Wikipedia offers full-text search to its users, the accuracy of its relevance-based search can be compromised by poor quality articles edited by non-experts and inexperienced contributors. In this paper, we propose a framework that re-ranks Wikipedia search results considering article quality. We develop two quality measurement models, namely Basic and PeerReview, to derive article quality based on co-authoring data gathered from articles' edit history. Compared with Wikipedia's full-text search engine, Google and Wikiseek, our experimental results showed that (i) quality-only ranking produced by PeerReview gives …
Comment-Oriented Blog Summarization By Sentence Extraction, Meishan Hu, Ee Peng Lim, Aixin Sun
Comment-Oriented Blog Summarization By Sentence Extraction, Meishan Hu, Ee Peng Lim, Aixin Sun
Research Collection School Of Computing and Information Systems
Much existing research on blogs focused on posts only, ignoring their comments. Our user study conducted on summarizing blog posts, however, showed that reading comments does change one's understanding about blog posts. In this research, we aim to extract representative sentences from a blog post that best represent the topics discussed among its comments. The proposed solution first derives representative words from comments and then selects sentences containing representative words. The representativeness of words is measured using ReQuT (i.e., Reader, Quotation, and Topic). Evaluated on human labeled sentences, ReQuT together with summation-based sentence selection showed promising results.
Measuring Article Quality In Wikipedia: Models And Evaluation, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady W. Lauw, Ba-Quy Vuong
Measuring Article Quality In Wikipedia: Models And Evaluation, Meiqun Hu, Ee Peng Lim, Aixin Sun, Hady W. Lauw, Ba-Quy Vuong
Research Collection School Of Computing and Information Systems
Wikipedia has grown to be the world largest and busiest free encyclopedia, in which articles are collaboratively written and maintained by volunteers online. Despite its success as a means of knowledge sharing and collaboration, the public has never stopped criticizing the quality of Wikipedia articles edited by non-experts and inexperienced contributors. In this paper, we investigate the problem of assessing the quality of articles in collaborative authoring of Wikipedia. We propose three article quality measurement models that make use of the interaction data between articles and their contributors derived from the article edit history. Our Basic model is designed based …
Important Characteristics Of Software Development Team Members: An Empirical Investigation Using Repertory Grid, Keng Siau, Xin Tan, Hong Sheng
Important Characteristics Of Software Development Team Members: An Empirical Investigation Using Repertory Grid, Keng Siau, Xin Tan, Hong Sheng
Research Collection School Of Computing and Information Systems
An information system is typically developed by a team of information systems (IS) professionals. Research shows that teams staffed with the right people are more likely to be effective and efficient. There is a paucity of study that examines the important traits of IS professionals in team contexts. The objective of this research is to identify and understand the important characteristics of good team members in software development projects. We applied an established psychological technique (Repertory Grid) to guide our interviews with 21 experienced IS professionals, who have had extensive experience in software development teams. The comprehensive list of important …
Important Characteristics Of Software Development Team Members: An Empirical Investigation Using Repertory Grid, Keng Siau, Xin Tan, Hong Sheng
Important Characteristics Of Software Development Team Members: An Empirical Investigation Using Repertory Grid, Keng Siau, Xin Tan, Hong Sheng
Research Collection School Of Computing and Information Systems
An information system is typically developed by a team of information systems (IS) professionals. Research shows that teams staffed with the right people are more likely to be effective and efficient. There is a paucity of study that examines the important traits of IS professionals in team contexts. The objective of this research is to identify and understand the important characteristics of good team members in software development projects. We applied an established psychological technique (Repertory Grid) to guide our interviews with 21 experienced IS professionals, who have had extensive experience in software development teams. The comprehensive list of important …
Reduce Response Time: Get "Hooked" On A Wiki, Rebecca Klein, Matthew Smith, David Sierkowski
Reduce Response Time: Get "Hooked" On A Wiki, Rebecca Klein, Matthew Smith, David Sierkowski
Information Technology Faculty and Staff Publications
Managing the flow of information both within the IT department and to our customers is one of our greatest challenges in the Office of Technology Information at Valparaiso University. To be successful, IT staff first need to acquire the right information from colleagues to provide excellent service. Then, the staff must determine the most effective way to communicate that information to internal and external customers to encourage the flow of information. To advance the IT department’s goals, how best can we utilize “information” and “communication” vehicles to exchange information, improve workflow, and ultimately communicate essential information to our internal and …
A Multi-Objective Genetic Algorithm That Employs A Hybrid Approach For Isolating Codon Usage Bias Indicative Of Translational Efficiency, Douglas W. Raiford, Dan E. Krane, Travis E. Doom, Michael L. Raymer
A Multi-Objective Genetic Algorithm That Employs A Hybrid Approach For Isolating Codon Usage Bias Indicative Of Translational Efficiency, Douglas W. Raiford, Dan E. Krane, Travis E. Doom, Michael L. Raymer
Kno.e.sis Publications
Isolation of translational efficiency bias can have important applications in gene expression prediction and heterologous protein production. In some genomes the presence of a high GC(AT)-content bias can confound the isolation of translational efficiency bias. In other organisms translational efficiency bias is weak making it difficult to isolate. Described here is a multi-objective genetic algorithm that improves the isolation of translational efficiency bias in Streptomyces coelicolor A3(2) and Pseudomonas aeruginosa PAO1, two organisms shown to have high GC-content and weak translational efficiency bias.
Swashup: Situational Web Applications Mashups, E. Michael Maximilien, Ajith Harshana Ranabahu, Stefan Tai
Swashup: Situational Web Applications Mashups, E. Michael Maximilien, Ajith Harshana Ranabahu, Stefan Tai
Kno.e.sis Publications
Distributed programming has shifted from private networks to the Internet using heterogeneous Web APIs. This enables the creation of situational applications of composed services exposing user interfaces, i.e., mashups. However, this programmable Web lacks unified models that can facilitate mashup creation, reuse, and deployments. This poster demonstrates a platform to facilitate Web 2.0 mashups.
A Proposed Statistical Protocol For The Analysis Of Metabolic Toxicological Data Derived From Nmr Spectroscopy, Benjamin J. Kelly, Paul E. Anderson, Nicholas V. Reo, Nicholas J. Delraso, Travis E. Doom, Michael L. Raymer
A Proposed Statistical Protocol For The Analysis Of Metabolic Toxicological Data Derived From Nmr Spectroscopy, Benjamin J. Kelly, Paul E. Anderson, Nicholas V. Reo, Nicholas J. Delraso, Travis E. Doom, Michael L. Raymer
Kno.e.sis Publications
Nuclear magnetic resonance (NMR) spectroscopy is a non-invasive method of acquiring a metabolic profile from biofluids. This metabolic information may provide keys to the early detection of exposure to a toxin. A typical NMR toxicology data set has low sample size and high dimensionality. Thus, traditional pattern recognition techniques are not always feasible. In this paper, we evaluate several common alternatives for isolating these biomarkers. The fold test, unpaired t-test, and paired t-test were performed on an NMR-derived toxicological data set and results were compared. The paired t-test method was preferred, due to its ability to attribute statistical significance, to …
Does Mutual Knowledge Affect Virtual Team Performance? Theoretical Analysis And Anecdotal Evidence, Alanah Davis, Deepak Khazanchi
Does Mutual Knowledge Affect Virtual Team Performance? Theoretical Analysis And Anecdotal Evidence, Alanah Davis, Deepak Khazanchi
Information Systems and Quantitative Analysis Faculty Publications
This paper describes the concept of mutual knowledge and its potential impact on virtual team performance. Based on an analysis of extant literature, we argue that there is a gap in our understanding of what is known about mutual knowledge as it impacts team dynamics and virtual team performance. Supporting literature, anecdotes, and case studies are used to discuss the importance of mutual knowledge for virtual team performance and the research issues that need to be addressed in the future.
Product Complexity: A Definition And Impacts On Operations, Mark A. Jacobs
Product Complexity: A Definition And Impacts On Operations, Mark A. Jacobs
MIS/OM/DS Faculty Publications
The difficulty for organizations arises because neither complexity nor its impacts on performance are well understood (Fisher & Ittner, 1999b). The mechanisms through which it affects cost, quality, delivery, and flexibility need to be explained (Ramdas, 2003). However, this cannot happen until complexity can be explained theoretically. But, to build theory there must first be a common understanding about the construct of interest (Wacker, 2004). Only then can researchers operationalize it and search for meaningful relationships. In light of this, I develop a definition of complexity below. A sampling of the operations management literature is then presented within the context …
Om-Based Video Shot Retrieval By One-To-One Matching, Yuxin Peng, Chong-Wah Ngo, Jianguo Xiao
Om-Based Video Shot Retrieval By One-To-One Matching, Yuxin Peng, Chong-Wah Ngo, Jianguo Xiao
Research Collection School Of Computing and Information Systems
This paper proposes a new approach for shot-based retrieval by optimal matching (OM), which provides an effective mechanism for the similarity measure and ranking of shots by one-to-one matching. In the proposed approach, a weighted bipartite graph is constructed to model the color similarity between two shots. Then OM based on Kuhn-Munkres algorithm is employed to compute the maximum weight of a constructed bipartite graph as the shot similarity value by one-to-one matching among frames. To improve the speed efficiency of OM, two improved algorithms are also proposed: bipartite graph construction based on subshots and bipartite graph construction based on …
I Tube, You Tube, Everybody Tubes: Analyzing The World’S Largest User Generated Content Video System, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue. Moon
I Tube, You Tube, Everybody Tubes: Analyzing The World’S Largest User Generated Content Video System, Meeyoung Cha, Haewoon Kwak, Pablo Rodriguez, Yong-Yeol Ahn, Sue. Moon
Research Collection School Of Computing and Information Systems
User Generated Content (UGC) is re-shaping the way people watch video and TV, with millions of video producers and consumers. In particular, UGC sites are creating new viewing patterns and social interactions, empowering users to be more creative, and developing new business opportunities. To better understand the impact of UGC systems, we have analyzed YouTube, the world's largest UGC VoD system. Based on a large amount of data collected, we provide an in-depth study of YouTube and other similar UGC systems. In particular, we study the popularity life-cycle of videos, the intrinsic statistical properties of requests and their relationship with …
Efficient Discovery Of Frequent Approximate Sequential Patterns, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
Efficient Discovery Of Frequent Approximate Sequential Patterns, Feida Zhu, Xifeng Yan, Jiawei Han, Philip S. Yu
Research Collection School Of Computing and Information Systems
We propose an efficient algorithm for mining frequent approximate sequential patterns under the Hamming distance model. Our algorithm gains its efficiency by adopting a "break-down-and-build-up" methodology. The "breakdown" is based on the observation that all occurrences of a frequent pattern can be classified into groups, which we call strands. We developed efficient algorithms to quickly mine out all strands by iterative growth. In the "build-up" stage, these strands are grouped up to form the support sets from which all approximate patterns would be identified. A salient feature of our algorithm is its ability to grow the frequent patterns by iteratively …
A Multitude Of Opinions: Mining Online Rating Data, Hady Wirawan Lauw, Ee Peng Lim
A Multitude Of Opinions: Mining Online Rating Data, Hady Wirawan Lauw, Ee Peng Lim
Research Collection School Of Computing and Information Systems
Online rating system is a popular feature of Web 2.0 applications. It typically involves a set of reviewers assigning rating scores (based on various evaluation criteria) to a set of objects. We identify two objectives for research on online rating data, namely achieving effective evaluation of objects and learning behaviors of reviewers/objects. These two objectives have conventionally been pursued separately. We argue that the future research direction should focus on the integration of these two objectives, as well as the integration between rating data and other types of data.
Gapprox: Mining Frequent Approximate Patterns From A Massive Network, Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
Gapprox: Mining Frequent Approximate Patterns From A Massive Network, Chen Chen, Xifeng Yan, Feida Zhu, Jiawei Han
Research Collection School Of Computing and Information Systems
Recently, there arise a large number of graphs with massive sizes and complex structures in many new applications, such as biological networks, social networks, and the Web, demanding powerful data mining methods. Due to inherent noise or data diversity, it is crucial to address the issue of approximation, if one wants to mine patterns that are potentially interesting with tolerable variations. In this paper, we investigate the problem of mining frequent approximate patterns from a massive network and propose a method called gApprox. gApprox not only finds approximate network patterns, which is the key for many knowledge discovery applications on …