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Articles 31 - 60 of 84
Full-Text Articles in OS and Networks
Semantics To Energize The Full Services Spectrum: Ontological Approach To Better Exploit Services At Technical And Business Levels, Amit P. Sheth
Semantics To Energize The Full Services Spectrum: Ontological Approach To Better Exploit Services At Technical And Business Levels, Amit P. Sheth
Kno.e.sis Publications
Services are pervasive in today’s economic landscape, and services- based architectures are being rapidly adopted as IT infrastructure. The need to take a broader perspective of services to include people and organizational descriptions as opposed to technical interface descriptions has already been recognized as part of an overall vision of services science [46, 100]. This article describes the Semantic Services Science (3S) model, which seeks to demonstrate the essential benefits of semantics in view of the broader vision of services science by using service descriptions that capture technical, human, organizational, and business value aspects. We assert that ontology-based semantic modeling …
Quo Vadis, Cs? – On The (Non)-Impact Of Conceptual Structures On The Semantic Web, Sebastian Rudolph, Markus Krotzsch, Pascal Hitzler
Quo Vadis, Cs? – On The (Non)-Impact Of Conceptual Structures On The Semantic Web, Sebastian Rudolph, Markus Krotzsch, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Conceptual Structures is a field of research which shares abstract concepts and interests with recent work on knowledge representation for the Semantic Web. However, while the latter is an area of research and development which is rapidly expanding in recent years, the former fails to participate in these developments on a large scale. In this paper, we attempt to stimulate the Conceptual Structures community to catch the Semantic Web train.
A Semantic Framework For Identifying Events In A Service Oriented Architecture, Karthik Gomadam, Ajith Harshana Ranabahu, Lakshmish Ramaswamy, Amit P. Sheth, Kunal Verma
A Semantic Framework For Identifying Events In A Service Oriented Architecture, Karthik Gomadam, Ajith Harshana Ranabahu, Lakshmish Ramaswamy, Amit P. Sheth, Kunal Verma
Kno.e.sis Publications
We propose a semantic framework for automatically identifying events as a step towards developing an adaptive middleware for Service Oriented Architecture (SOA). Current related research focuses on adapting to events that violate certain non-functional objectives of the service requestor. Given the large of number of events that can happen during the execution of a service, identifying events that can impact the non-functional objectives of a service request is a key challenge. To address this problem we propose an approach that allows service requestors to create semantically rich service requirement descriptions, called semantic templates. We propose a formal model for expressing …
Relationship Web: Realizing The Memex Vision With The Help Of Semantic Web, Amit P. Sheth
Relationship Web: Realizing The Memex Vision With The Help Of Semantic Web, Amit P. Sheth
Kno.e.sis Publications
Relationship Web takes us from "which document" could have information I need to "what's in the resources" that gives me the insight and knowledge I need for decision making. Dr. Vannevar Bush outlined his vision for Memex in a 1945 Atlantic Monthly article [1]. Describing how the human brain navigates an information space in what he called trailblazing, Dr. Bush said, "It operates by association. With one item in its grasp, it snaps instantly to the next that is suggested by the association of thoughts, in accordance with some intricate web of trails carried by the cells of the brain." …
Semantics To Empower Services Science: Using Semantics At Middleware, Web Services And Business Levels, Amit P. Sheth
Semantics To Empower Services Science: Using Semantics At Middleware, Web Services And Business Levels, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Runtime Support Of Speculative Optimization For Offline Escape Analysis, Kevin Cleereman, Michelle Cheatham, Krishnaprasad Thirunarayan
Runtime Support Of Speculative Optimization For Offline Escape Analysis, Kevin Cleereman, Michelle Cheatham, Krishnaprasad Thirunarayan
Kno.e.sis Publications
Escape analysis can improve the speed and memory efficiency of garbage collected languages by allocating objects to the call stack, but an offline analysis will potentially interfere with dynamic class loading and an online analysis must sacrifice precision for speed. We describe a technique that permits the safe use of aggressive, speculative offline escape analysis in programs potentially loading classes that violate the analysis results.
Paraconsistent Resolution For Four-Valued Description Logics, Yue Ma, Pascal Hitzler, Zuoquan Li
Paraconsistent Resolution For Four-Valued Description Logics, Yue Ma, Pascal Hitzler, Zuoquan Li
Computer Science and Engineering Faculty Publications
In this paper, we propose an approach to translating any ALC ontology (possible inconsistent) into a logically consistent set of disjunctive datalog rules. We achieve this in two steps: First we give a simple way to make any ALC based ontology 4-valued satisfiable, and then we study a sound and complete paraconsistent ordered-resolution decision procedure for our 4-valued ALC. Our approach can be viewed as a paraconsistent version of KAON2 algorithm.
Measuring Inconsistency For Description Logics Based On Paraconsistent Semantics, Yue Ma, Guilin Qi, Pascal Hitzler, Zuoquan Lin
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.
Foundations Of Refinement Operators For Description Logics, Jens Lehmann, Pascal Hitzler
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 …
A Refinement Operator Based Learning Algorithm For The Alc Description Logic, Jens Lehmann, Pascal Hitzler
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.
Selecting Labels For News Document Clusters, Krishnaprasad Thirunarayan, Trivikram Immaneni, Mastan Vali Shaik
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 …
Acquisition Of Owl Dl Axioms From Lexical Resources, Johanna Volker, Pascal Hitzler, Philipp Cimiano
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 …
Algorithms For Paraconsistent Reasoning With Owl, Yue Ma, Pascal Hitzler, Zuoquan Lin
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 …
A Well-Founded Semantics For Hybrid Mknf Knowledge Bases, Matthias Knorr, Jose Julio Alferes, Pascal Hitzler
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.
Efficient Owl Reasoning With Logic Programs - Evaluations, Sebastian Rudolph, Markus Krotzsch, Pascal Hitzler, Michael Sintek, Denny Vrandecic
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.
Automatic Composition Of Semantic Web Services Using Process Mediation, Zixin Wu, Karthik Gomadam, Ajith Harshana Ranabahu, Amit P. Sheth, John A. Miller
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. …
Using Sawsdl For Semantic Service Interoperability, Kunal Verma, Amit P. Sheth
Using Sawsdl For Semantic Service Interoperability, Kunal Verma, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Semantic Annotations For Wsdl, Amit P. Sheth, Jacek Kopecky
Semantic Annotations For Wsdl, Amit P. Sheth, Jacek Kopecky
Kno.e.sis Publications
No abstract provided.
Estimating The Cardinality Of Rdf Graph Patterns, Angela Maduko, Kemafor Anyanwu, Amit P. Sheth, Paul Schliekelman
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.
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
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.
Semantic Web: Technologies And Applications For The Real-World, Amit P. Sheth
Semantic Web: Technologies And Applications For The Real-World, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Visualization Of Events In A Spatially And Multimedia Enriched Virtual Environment, Leonidas Deligiannidis, Farshad Hakimpour, Amit P. Sheth
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. …
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
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 …
Residual-Based Measurement Of Peer And Link Lifetimes In Gnutella Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Residual-Based Measurement Of Peer And Link Lifetimes In Gnutella Networks, Xiaoming Wang, Zhongmei Yao, Dmitri Loguinov
Computer Science Faculty Publications
Existing methods of measuring lifetimes in P2P systems usually rely on the so-called create-based method (CBM), which divides a given observation window into two halves and samples users "created" in the first half every Delta time units until they die or the observation period ends. Despite its frequent use, this approach has no rigorous accuracy or overhead analysis in the literature. To shed more light on its performance, we flrst derive a model for CBM and show that small window size or large Delta may lead to highly inaccurate lifetime distributions. We then show that create-based sampling exhibits an inherent …
On Node Isolation Under Churn In Unstructured P2p Networks With Heavy-Tailed Lifetimes, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov
On Node Isolation Under Churn In Unstructured P2p Networks With Heavy-Tailed Lifetimes, Zhongmei Yao, Xiaoming Wang, Dmitri Loguinov
Computer Science Faculty Publications
Previous analytical studies [12], [18] of unstructured P2P resilience have assumed exponential user lifetimes and only considered age-independent neighbor replacement. In this paper, we overcome these limitations by introducing a general node-isolation model for heavy-tailed user lifetimes and arbitrary neighbor-selection algorithms. Using this model, we analyze two age-biased neighbor-selection strategies and show that they significantly improve the residual lifetimes of chosen users, which dramatically reduces the probability of user isolation and graph partitioning compared to uniform selection of neighbors. In fact, the second strategy based on random walks on age-weighted graphs demonstrates that for lifetimes with infinite variance, the system …
Semantic Web Applications In Industry, Government, Health Care And Life Sciences, Amit P. Sheth
Semantic Web Applications In Industry, Government, Health Care And Life Sciences, Amit P. Sheth
Kno.e.sis Publications
No abstract provided.
Spatiotemporal And Thematic Semantic Analytics, Matthew Perry
Spatiotemporal And Thematic Semantic Analytics, Matthew Perry
Kno.e.sis Publications
No abstract provided.
Towards Attack-Resilient Geometric Data Perturbation, Keke Chen, Ling Liu
Towards Attack-Resilient Geometric Data Perturbation, Keke Chen, Ling Liu
Kno.e.sis Publications
Data perturbation is a popular technique for privacy-preserving data mining. The major challenge of data perturbation is balancing privacy protection and data quality, which are normally considered as a pair of contradictive factors. We propose that selectively preserving only the task/model specific information in perturbation would improve the balance. Geometric data perturbation, consisting of random rotation perturbation, random translation perturbation, and noise addition, aims at preserving the important geometric properties of a multidimensional dataset, while providing better privacy guarantee for data classification modeling. The preliminary study has shown that random geometric perturbation can well preserve model accuracy for several popular …
Mining Minimal Distinguishing Subsequence Patterns With Gap Constraints, Xiaonan Ji, James Bailey, Guozhu Dong
Mining Minimal Distinguishing Subsequence Patterns With Gap Constraints, Xiaonan Ji, James Bailey, Guozhu Dong
Kno.e.sis Publications
Discovering contrasts between collections of data is an important task in data mining. In this paper, we introduce a new type of contrast pattern, called a Minimal Distinguishing Subsequence (MDS). An MDS is a minimal subsequence that occurs frequently in one class of sequences and infrequently in sequences of another class. It is a natural way of representing strong and succinct contrast information between two sequential datasets and can be useful in applications such as protein comparison, document comparison and building sequential classification models. Mining MDS patterns is a challenging task and is significantly different from mining contrasts between relational/transactional …
Stochastic Estimation And Control Of Queues Within A Computer Network, Nathan C. Stuckey
Stochastic Estimation And Control Of Queues Within A Computer Network, Nathan C. Stuckey
Theses and Dissertations
An extended Kalman filter is used to estimate size and packet arrival rate of network queues. These estimates are used by a LQG steady state linear perturbation PI controller to regulate queue size within a computer network. This paper presents the derivation of the transient queue behavior for a system with Poisson traffic and exponential service times. This result is then validated for ideal traffic using a network simulated in OPNET. A more complex OPNET model is then used to test the adequacy of the transient queue size model when non-Poisson traffic is combined. The extended Kalman filter theory is …