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- Keyword
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- Semantic Web (8)
- SAWSDL (5)
- Semantic Web Services (5)
- SSW (3)
- Semantic web (3)
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- WSDL-S (3)
- Data Integration (2)
- Entrez Gene (2)
- Gene Ontology (2)
- Mashups (2)
- Ontology (2)
- RDF (2)
- Relationship Web (2)
- SA-REST (2)
- SPARQL (2)
- Semantic Analytics (2)
- Semantic Sensor Web (2)
- Web 2.0 (2)
- Abductive Inference (1)
- Adaptive Web Process (1)
- Adaptive Web Service (1)
- Autoepistemic DLs (1)
- Automatic Refactoring (1)
- Autonomic Web Process (1)
- Autonomic Web Service (1)
- Background domain knowledge (1)
- Circumscriptive Dls (1)
- Contrast Pattern (1)
- DSLs (1)
- Data Cube (1)
Articles 31 - 60 of 73
Full-Text Articles in Physical Sciences and Mathematics
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. …
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.
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 …
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.
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 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.
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 …
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.
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 …
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.
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 …
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.
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 …
Spatiotemporal And Thematic Semantic Analytics, Matthew Perry
Spatiotemporal And Thematic Semantic Analytics, Matthew Perry
Kno.e.sis Publications
No abstract provided.
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 …
Automatic Composition Of Semantic Web Services Using Process And Data Mediation, Zixin Wu, Ajith H. Ranabahu, Karthik Gomadam, Amit P. Sheth, John A. Miller
Automatic Composition Of Semantic Web Services Using Process And Data Mediation, Zixin Wu, Ajith H. Ranabahu, Karthik Gomadam, 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. …
Engineering Mathematics Education At Wright State University: Uncorking The First Year Bottleneck, Nathan W. Klingbeil, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds, Richard Mercer
Engineering Mathematics Education At Wright State University: Uncorking The First Year Bottleneck, Nathan W. Klingbeil, Kuldip S. Rattan, Michael L. Raymer, David B. Reynolds, Richard Mercer
Kno.e.sis Publications
No abstract provided.
Data Integration, Meenakshi Nagarajan
Glycoo Ontology, Christopher Thomas
Sensor Networks Survey, Cory Andrew Henson, Satya S. Sahoo
Sensor Networks Survey, Cory Andrew Henson, Satya S. Sahoo
Kno.e.sis Publications
No abstract provided.
Semantic Matchmaking Of Web Resources With Local Closed-World Reasoning, Stephan Grimm, Pascal Hitzler
Semantic Matchmaking Of Web Resources With Local Closed-World Reasoning, Stephan Grimm, Pascal Hitzler
Computer Science and Engineering Faculty Publications
Ontology languages like OWL allow for semantically rich annotation of resources (e.g., products advertised at on-line electronic marketplaces). The description logic (DL) formalism underlying OWL provides reasoning techniques that perform match-making on such annotations. This paper identifies peculiarities in the use of DL inferences for matchmaking that derive from OWL's open-world semantics, analyzes local closed-world reasoning for its applicability to matchmaking, and investigates the suitability of two nonmonotonic extensions to DL, autoepistemic DLs and DLs with circumscription, for local closed-world reasoning in the matchmaking context. An elaborate example of an electronic marketplace for PC product catalogs from the e-commerce domain …
Measuring Inconsistency For Description Logics Based On Paraconsistent Semantics, Yue Ma, Guilin Qi, Pascal Hitzler, Zuoquan Li
Measuring Inconsistency For Description Logics Based On Paraconsistent Semantics, Yue Ma, Guilin Qi, Pascal Hitzler, Zuoquan Li
Computer Science and Engineering Faculty Publications
In this paper, we present an approach for measuring inconsistency in a knowledge base. We first define the degree of inconsistency using a four-valued semantics for the description logic ALC. Then an ordering over knowledge bases is given by considering their inconsistency degrees. Our measure of inconsistency can provide important information for inconsistency handling.
Glycomics Project Overview, Satya S. Sahoo
Glycomics Project Overview, Satya S. Sahoo
Kno.e.sis Publications
No abstract provided.