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Articles 5851 - 5880 of 7256

Full-Text Articles in Computer Sciences

Measuring Inconsistency For Description Logics Based On Paraconsistent Semantics, Yue Ma, Guilin Qi, Pascal Hitzler, Zuoquan Lin Jun 2007

Measuring Inconsistency For Description Logics Based On Paraconsistent Semantics, Yue Ma, Guilin Qi, Pascal Hitzler, Zuoquan Lin

Computer Science and Engineering Faculty Publications

In this paper, we propose an approach for measuring inconsistency in inconsistent ontologies. We first define the degree of inconsistency of an inconsistent ontology using a four-valued semantics for the description logic ALC. Then an ordering over inconsistent ontologies is given by considering their inconsistency degrees. Our measure of inconsistency can provide important information for inconsistency handling.

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Foundations Of Refinement Operators For Description Logics, Jens Lehmann, Pascal Hitzler Jun 2007

Foundations Of Refinement Operators For Description Logics, Jens Lehmann, Pascal Hitzler

Computer Science and Engineering Faculty Publications

In order to leverage techniques from Inductive Logic Programming for the learning in description logics (DLs), which are the foundation of ontology languages in the Semantic Web, it is important to acquire a thorough understanding of the theoretical potential and limitations of using refinement operators within the description logic paradigm. In this paper, we present a comprehensive study which analyses desirable properties such operators should have. In particular, we show that ideal refinement operators in general do not exist, which is indicative of the hardness inherent in learning in DLs. We also show which combinations of desirable properties are theoretically …

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A Refinement Operator Based Learning Algorithm For The Alc Description Logic, Jens Lehmann, Pascal Hitzler Jun 2007

A Refinement Operator Based Learning Algorithm For The Alc Description Logic, Jens Lehmann, Pascal Hitzler

Computer Science and Engineering Faculty Publications

With the advent of the Semantic Web, description logics have become one of the most prominent paradigms for knowledge representation and reasoning. Progress in research and applications, however, faces a bottleneck due to the lack of available knowledge bases, and it is paramount that suitable automated methods for their acquisition will be developed. In this paper, we provide the first learning algorithm based on refinement operators for the most fundamental description logic ALC. We develop the algorithm from thorough theoretical foundations and report on a prototype implementation.

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Selecting Labels For News Document Clusters, Krishnaprasad Thirunarayan, Trivikram Immaneni, Mastan Vali Shaik Jun 2007

Selecting Labels For News Document Clusters, Krishnaprasad Thirunarayan, Trivikram Immaneni, Mastan Vali Shaik

Kno.e.sis Publications

This work deals with determination of meaningful and terse cluster labels for News document clusters. We analyze a number of alternatives for selecting headlines and/or sentences of document in a document cluster (obtained as a result of an entity-event-duration query), and formalize an approach to extracting a short phrase from well-supported headlines/sentences of the cluster that can serve as the cluster label. Our technique maps a sentence into a set of significant stems to approximate its semantics, for comparison. Eventually a cluster label is extracted from a selected headline/sentence as a contiguous sequence of words, resuscitating word sequencing information lost …

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Acquisition Of Owl Dl Axioms From Lexical Resources, Johanna Volker, Pascal Hitzler, Philipp Cimiano Jun 2007

Acquisition Of Owl Dl Axioms From Lexical Resources, Johanna Volker, Pascal Hitzler, Philipp Cimiano

Computer Science and Engineering Faculty Publications

State-of-the-art research on automated learning of ontologies from text currently focuses on inexpressive ontologies. The acquisition of complex axioms involving logical connectives, role restrictions, and other expressive features of the Web Ontology Language OWL remains largely unexplored. In this paper, we present a method and implementation for enriching inexpressive OWL ontologies with expressive axioms which is based on a deep syntactic analysis of natural language definitions. We argue that it can serve as a core for a semi-automatic ontology engineering process supported by a methodology that integrates methods for both ontology learning and evaluation. The feasibility of our approach is …

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Algorithms For Paraconsistent Reasoning With Owl, Yue Ma, Pascal Hitzler, Zuoquan Lin Jun 2007

Algorithms For Paraconsistent Reasoning With Owl, Yue Ma, Pascal Hitzler, Zuoquan Lin

Computer Science and Engineering Faculty Publications

In an open, constantly changing and collaborative environment like the forthcoming Semantic Web, it is reasonable to expect that knowledge sources will contain noise and inaccuracies. Practical reasoning techniques for ontologies therefore will have to be tolerant to this kind of data, including the ability to handle inconsistencies in a meaningful way. For this purpose, we employ paraconsistent reasoning based on four-valued logic, which is a classical method for dealing with inconsistencies in knowledge bases. Its transfer to OWL DL, however, necessitates the making of fundamental design choices in dealing with class inclusion, which has resulted in differing proposals for …

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A Well-Founded Semantics For Hybrid Mknf Knowledge Bases, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler Jun 2007

A Well-Founded Semantics For Hybrid Mknf Knowledge Bases, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler

Computer Science and Engineering Faculty Publications

In [10], hybrid MKNF knowledge bases have been proposed for combining open and closed world reasoning within the logics of minimal knowledge and negation as failure ([8]). For this powerful framework, we define a three-valued semantics and provide an alternating fixpoint construction for nondisjunctive hybrid MKNF knowledge bases. We thus provide a well-founded semantics which is a sound approximation of the cautious MKNF model semantics, and which also features improved computational properties. We also show that whenever the DL knowledge base part is empty, then the alternating fixpoint coincides with the classical well-founded model.

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Efficient Owl Reasoning With Logic Programs - Evaluations, Sebastian Rudolph, Markus Krotzsch, Pascal Hitzler, Michael Sintek, Denny Vrandecic Jun 2007

Efficient Owl Reasoning With Logic Programs - Evaluations, Sebastian Rudolph, Markus Krotzsch, Pascal Hitzler, Michael Sintek, Denny Vrandecic

Computer Science and Engineering Faculty Publications

We report on efficiency evaluations concerning two different approaches to using logic programming for OWL [1] reasoning and show, how the two approaches can be combined.

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Automatic Composition Of Semantic Web Services Using Process Mediation, Zixin Wu, Karthik Gomadam, Ajith Harshana Ranabahu, Amit P. Sheth, John A. Miller Jun 2007

Automatic Composition Of Semantic Web Services Using Process Mediation, Zixin Wu, Karthik Gomadam, Ajith Harshana Ranabahu, Amit P. Sheth, John A. Miller

Kno.e.sis Publications

Web service composition has quickly become a key area of research in the services oriented architecture community. One of the challenges in composition is the existence of heterogeneities across independently created and autonomously managed Web service requesters and Web service providers. Previous work in this area either involved significant human effort or in cases of the efforts seeking to provide largely automated approaches, overlooked the problem of data heterogeneities, resulting in partial solutions that would not support executable workflow for real-world problems. In this paper, we present a planning-based approach to solve both the process heterogeneity and data heterogeneity problems. …

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Assessing Organizational Innovation Capability And Its Effect On E-Commerce Initiatives, Ann L. Fruhling, Keng Siau Jun 2007

Assessing Organizational Innovation Capability And Its Effect On E-Commerce Initiatives, Ann L. Fruhling, Keng Siau

Research Collection School Of Computing and Information Systems

This research uses a qualitative approach to study the innovative capability of two organizations and the effect of innovation on their E-Commerce initiatives, strategies, and outcomes. The Innovation Strategy Model is used in this research to analyze the innovative capability of two organizations. The case study research methodology was selected and two case studies are presented. The research results show that one organization is more innovative than the other in terms of its innovative capability. A post-study follow-up shows that the organization that was high on innovative capability was very successful in their E-Commerce initiative whereas the other organization was …

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Can Uml Be Simplified? Practitioner Use Of Uml In Separate Domains, J. Erickson, Keng Siau Jun 2007

Can Uml Be Simplified? Practitioner Use Of Uml In Separate Domains, J. Erickson, Keng Siau

Research Collection School Of Computing and Information Systems

UML’s complexity is regularly criticized by practitioners and researchers alike, who argue that such complexity is a considerable detriment to the adoption and use of UML in the field. Attempts have been made to assess and/or measure UML’s complexity in a number of ways. Erickson and Siau proposed that a subset (kernel) of UML, composed of the most important constructs, could be equated with the complexity that practitioners face when using the modeling language. This research extends Erickson and Siau’s work by proposing a UML kernel in three application areas, real-time, webbased and enterprise systems. Compared to other modeling methods …

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Intelligence Through Interaction: Towards A Unified Theory For Learning, Ah-Hwee Tan, Gail A. Carpenter, Stephen Grossberg Jun 2007

Intelligence Through Interaction: Towards A Unified Theory For Learning, Ah-Hwee Tan, Gail A. Carpenter, Stephen Grossberg

Research Collection School Of Computing and Information Systems

Machine learning, a cornerstone of intelligent systems, has typically been studied in the context of specific tasks, including clustering (unsupervised learning), classification (supervised learning), and control (reinforcement learning). This paper presents a learning architecture within which a universal adaptation mechanism unifies a rich set of traditionally distinct learning paradigms, including learning by matching, learning by association, learning by instruction, and learning by reinforcement. In accordance with the notion of embodied intelligence, such a learning theory provides a computational account of how an autonomous agent may acquire the knowledge of its environment in a real-time, incremental, and continuous manner. Through a …

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The Multi-Agent Data Collection In Hla-Based Simulation System, Heng-Jie Song, Zhi-Qi Shen, Chunyan Miao, Ah-Hwee Tan, Guo-Peng Zhao Jun 2007

The Multi-Agent Data Collection In Hla-Based Simulation System, Heng-Jie Song, Zhi-Qi Shen, Chunyan Miao, Ah-Hwee Tan, Guo-Peng Zhao

Research Collection School Of Computing and Information Systems

The High Level Architecture (HLA) for distributed simulation was proposed by the Defense Modeling and Simulation Office of the Department of Defense (DOD) in order to support interoperability among simulations as well as reuse of simulation models. One aspect of reusability is to collect and analyze data generated in simulation exercises, including a record of events that occur during the execution, and the states of simulation objects. In order to improve the performance of existing data collection mechanisms in the HLA simulation system, the paper proposes a multi-agent data collection system. The proposed approach adopts the hierarchical data management/organization mechanism …

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A Hybrid Of Plot-Based And Character-Based Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen Jun 2007

A Hybrid Of Plot-Based And Character-Based Interactive Storytelling, Yundong Cai, Chunyan Miao, Ah-Hwee Tan, Zhiqi Shen

Research Collection School Of Computing and Information Systems

Interactive storytelling in the virtual environment attracts a lot of research interests in recent years. Story plot and character are two most important elements of a story. Based on these two elements, currently there are two research directions: plot-based and character-based interactive storytelling. However, plot-based approach lacks the refinement of character behaviors as character-based approach. On the other side, character-based approach does not follow a well organized story plot so that the moral of the story might be distorted. Therefore, there is a need to develop an integrated framework to achieve the balance between conveying story moral and enhancing the …

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Learning Nonparametric Kernel Matrices From Pairwise Constraints, Steven C. H. Hoi, Rong Jin, Michael R. Lyu Jun 2007

Learning Nonparametric Kernel Matrices From Pairwise Constraints, Steven C. H. Hoi, Rong Jin, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Many kernel learning methods have to assume parametric forms for the target kernel functions, which significantly limits the capability of kernels in fitting diverse patterns. Some kernel learning methods assume the target kernel matrix to be a linear combination of parametric kernel matrices. This assumption again importantly limits the flexibility of the target kernel matrices. The key challenge with nonparametric kernel learning arises from the difficulty in linking the nonparametric kernels to the input patterns. In this paper, we resolve this problem by introducing the graph Laplacian of the observed data as a regularizer when optimizing the kernel matrix with …

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A Multi-Scale Tikhonov Regularization Scheme For Implicit Surface Modeling, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu Jun 2007

A Multi-Scale Tikhonov Regularization Scheme For Implicit Surface Modeling, Jianke Zhu, Steven C. H. Hoi, Michael R. Lyu

Research Collection School Of Computing and Information Systems

Kernel machines have recently been considered as a promising solution for implicit surface modelling. A key challenge of machine learning solutions is how to fit implicit shape models from large-scale sets of point cloud samples efficiently. In this paper, we propose a fast solution for approximating implicit surfaces based on a multi-scale Tikhonov regularization scheme. The optimization of our scheme is formulated into a sparse linear equation system, which can be efficiently solved by factorization methods. Different from traditional approaches, our scheme does not employ auxiliary off-surface points, which not only saves the computational cost but also avoids the problem …

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Similarity Beyond Distance Measurement, Feng Kang, Rong Jin, Steven C. H. Hoi Jun 2007

Similarity Beyond Distance Measurement, Feng Kang, Rong Jin, Steven C. H. Hoi

Research Collection School Of Computing and Information Systems

One of the keys issues to content-based image retrieval is the similarity measurement of images. Images are represented as points in the space of low-level visual features and most similarity measures are based on certain distance measurement between these features. Given a distance metric, two images with shorter distance are deemed to more similar than images that are far away. The well-known problem with these similarity measures is the semantic gap, namely two images separated by large distance could share the same semantic content. In this paper, we propose a novel similarity measure of images that goes beyond the distance …

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Continuous Nearest Neighbor Queries Over Sliding Windows, Kyriakos Mouratidis, Dimitris Papadias Jun 2007

Continuous Nearest Neighbor Queries Over Sliding Windows, Kyriakos Mouratidis, Dimitris Papadias

Research Collection School Of Computing and Information Systems

Recent research has focused on continuous monitoring of nearest neighbors (NN) in highly dynamic scenarios, where the queries and the data objects move frequently and arbitrarily. All existing methods, however, assume the Euclidean distance metric. In this paper we study k-NN monitoring in road networks, where the distance between a query and a data object is determined by the length of the shortest path connecting them. We propose two methods that can handle arbitrary object and query moving patterns, as well as fluctuations of edge weights. The first one maintains the query results by processing only updates that may invalidate …

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Instance Weighting For Domain Adaptation In Nlp, Jing Jiang, Chengxiang Zhai Jun 2007

Instance Weighting For Domain Adaptation In Nlp, Jing Jiang, Chengxiang Zhai

Research Collection School Of Computing and Information Systems

Domain adaptation is an important problem in natural language processing (NLP) due to the lack of labeled data in novel domains. In this paper, we study the domain adaptation problem from the instance weighting per- spective. We formally analyze and charac- terize the domain adaptation problem from a distributional view, and show that there are two distinct needs for adaptation, cor- responding to the different distributions of instances and classification functions in the source and the target domains. We then propose a general instance weighting frame- work for domain adaptation. Our empir- ical results on three NLP tasks show that …

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Mobile G-Portal Supporting Collaborative Sharing And Learning In Geography Fieldwork: An Empirical Study, Yin-Leng Theng, Kuah-Li Tan, Ee Peng Lim, Jun Zhang, Dion Hoe-Lian Goh, Kalyani Chatterjea, Chew-Hung Chang, Aixin Sun, Han Yu, Nam Hai Dang, Yuanyuan Li, Minh Chanh Vo Jun 2007

Mobile G-Portal Supporting Collaborative Sharing And Learning In Geography Fieldwork: An Empirical Study, Yin-Leng Theng, Kuah-Li Tan, Ee Peng Lim, Jun Zhang, Dion Hoe-Lian Goh, Kalyani Chatterjea, Chew-Hung Chang, Aixin Sun, Han Yu, Nam Hai Dang, Yuanyuan Li, Minh Chanh Vo

Research Collection School Of Computing and Information Systems

Integrated with G-Portal, a Web-based geospatial digital library of geography resources, this paper describes the implementation of Mobile G-Portal, a group of mobile devices as learning assistant tools supporting collaborative sharing and learning for geography fieldwork. Based on a modified Technology Acceptance Model and a Task-Technology Fit model, an initial study with Mobile G-Portal was conducted involving 39 students in a local secondary school. The findings suggested positive indication of acceptance of Mobile G-Portal for geography fieldwork. The paper concludes with a discussion on technological challenges, recommendations for refinement of Mobile G-Portal, and design implications in general for digital libraries …

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People-Search : Searching For People Sharing Similar Interests From The Web, Quanzhi Li May 2007

People-Search : Searching For People Sharing Similar Interests From The Web, Quanzhi Li

Dissertations

On the Web, there are limited ways of finding people sharing similar interests or background with a given person. The current methods, such as using regular search engines, are either ineffective or time consuming. In this work, a new approach for searching people sharing similar interests from the Web, called People-Search, is presented. Given a person, to find similar people from the Web, there are two major research issues: person representation and matching persons. In this study, a person representation method which uses a person's website to represent this person's interest and background is proposed. The design of matching process …

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Sifting Customers From The Clickstream : Behavior Pattern Discovery In A Virtual Shopping Environment, Peishih Chang May 2007

Sifting Customers From The Clickstream : Behavior Pattern Discovery In A Virtual Shopping Environment, Peishih Chang

Dissertations

While shopping online, customers' needs and goals may change dynamically, based on a variety of factors such as product information and characteristics, time pressure and perceived risk. While these changes create emergent information needs, decisions about what information to present to customers are typically made before customers have visited a web site, using data such as purchase histories and logs of web pages visited. Better understanding of customer cognition and behavior as a function of various factors is needed in order to enable the right information to be presented at the right time. One approach to achieving this understanding is …

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Using Sawsdl For Semantic Service Interoperability, Kunal Verma, Amit P. Sheth May 2007

Using Sawsdl For Semantic Service Interoperability, Kunal Verma, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Semantic Annotations For Wsdl, Amit P. Sheth, Jacek Kopecky May 2007

Semantic Annotations For Wsdl, Amit P. Sheth, Jacek Kopecky

Kno.e.sis Publications

No abstract provided.

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Estimating The Cardinality Of Rdf Graph Patterns, Angela Maduko, Kemafor Anyanwu, Amit P. Sheth, Paul Schliekelman May 2007

Estimating The Cardinality Of Rdf Graph Patterns, Angela Maduko, Kemafor Anyanwu, Amit P. Sheth, Paul Schliekelman

Kno.e.sis Publications

Most RDF query languages allow for graph structure search through a conjunction of triples which is typically processed using join operations. A key factor in optimizing joins is determining the join order which depends on the expected cardinality of intermediate results. This work proposes a pattern-based summarization framework for estimating the cardinality of RDF graph patterns. We present experiments on real world and synthetic datasets which confirm the feasibility of our approach.

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Altering Document Term Vectors For Classification - Ontologies As Expectations Of Co-Occurrence, Meenakshi Nagarajan, Amit P. Sheth, Marcos Aguilera, Kimberly Keeton, Arif Merchant, Mustafa Uysal May 2007

Altering Document Term Vectors For Classification - Ontologies As Expectations Of Co-Occurrence, Meenakshi Nagarajan, Amit P. Sheth, Marcos Aguilera, Kimberly Keeton, Arif Merchant, Mustafa Uysal

Kno.e.sis Publications

In this paper we extend the state-of-the-art in utilizing background knowledge for supervised classification by exploiting the semantic relationships between terms explicated in Ontologies. Preliminary evaluations indicate that the new approach generally improves precision and recall, more so for hard to classify cases and reveals patterns indicating the usefulness of such background knowledge.

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Semantic Web: Technologies And Applications For The Real-World, Amit P. Sheth May 2007

Semantic Web: Technologies And Applications For The Real-World, Amit P. Sheth

Kno.e.sis Publications

No abstract provided.

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Visualization Of Events In A Spatially And Multimedia Enriched Virtual Environment, Leonidas Deligiannidis, Farshad Hakimpour, Amit P. Sheth May 2007

Visualization Of Events In A Spatially And Multimedia Enriched Virtual Environment, Leonidas Deligiannidis, Farshad Hakimpour, Amit P. Sheth

Kno.e.sis Publications

Semantic Event Tracker (SET) is a highly interactive visualization tool for tracking and associating activities (events) in a spatially and Multimedia Enriched Virtual Environment. SET provides integrated views of information spaces while providing overview and detail to improve perception and evaluation of complex scenarios. We model an event as an object that describes an action and its location, time, and relations to other objects. Real world event information is extracted from Internet sources, then stored and processed using Semantic Web technologies that enable us to discover semantic associations between events. We use RDF graphs to represent semantic metadata and ontologies. …

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An Experiment In Integrating Large Biomedical Knowledge Resources With Rdf: Application To Associating Genotype And Phenotype Information, Satya S. Sahoo, Olivier Bodenreider, Kelly Zeng, Amit P. Sheth May 2007

An Experiment In Integrating Large Biomedical Knowledge Resources With Rdf: Application To Associating Genotype And Phenotype Information, Satya S. Sahoo, Olivier Bodenreider, Kelly Zeng, Amit P. Sheth

Kno.e.sis Publications

Bridging between genotype and phenotype is generally achieved through the integration of knowledge sources such as Entrez Gene (EG), Online Mendelian Inheritance in Man (OMIM) and the Gene Ontology (GO). Traditionally, such integration implies manual effort or the development of customized software. In this paper, we demonstrate how the Resource Description Framework (RDF) can be used to represent and integrate these resources and support complex queries over the unified resource. We illustrate the effectiveness of our approach by answering a real-world biomedical query linking a specific molecular function, glycosyltransferase, to the disorder congenital muscular dystrophy, which potentially forms a new …

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The Influence Of Transactive Memory On Mutual Knowledge In Virtual Teams: A Theoretical Proposal, Alanah Davis, Deepak Khazanchi May 2007

The Influence Of Transactive Memory On Mutual Knowledge In Virtual Teams: A Theoretical Proposal, Alanah Davis, Deepak Khazanchi

Information Systems and Quantitative Analysis Faculty Proceedings & Presentations

Advancements in information technologies (IT) have enabled the ability to exchange knowledge within and across organizations through virtual teams. However, the ability to effectively communicate and share knowledge in virtual settings can become a difficult task due to the complex nature of both the virtual context and the technology used to support them. This paper argues that transactive memory theory can explain how mutual knowledge enhances virtual team performance. We present a conceptual model and theoretical propositions for the study of the relationship between transactive memory and mutual knowledge in virtual teams.

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