Topic
Ontology-based data integration
About: Ontology-based data integration is a research topic. Over the lifetime, 11065 publications have been published within this topic receiving 216888 citations.
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TL;DR: It is argued that a useful ontology must simultaneously strive for usability and reusability and explain how these goals are achieved by OntoCAPE.
121 citations
Book•
01 Jan 2006
TL;DR: The Semantic Web: A Network of Understanding, Transformation from OWL Description to Resource Space Model, and Next GenerationSemantic Web Applications.
Abstract: Invited Talks.- The Semantic Web: A Network of Understanding.- Transformation from OWL Description to Resource Space Model.- Next Generation Semantic Web Applications.- Annotation.- Hierarchical Topic Term Extraction for Semantic Annotation in Chinese Bulletin Board System.- Automatic Annotation Using Citation Links and Co-citation Measure: Application to the Water Information System.- Semantic Annotation Using Horizontal and Vertical Contexts.- Semantic Wiki as a Lightweight Knowledge Management System.- Ontology Alignment.- Partition-Based Block Matching of Large Class Hierarchies.- Towards Quick Understanding and Analysis of Large-Scale Ontologies.- Matching Large Scale Ontology Effectively.- Finding Important Vocabulary Within Ontology.- Document and Recommendation.- Ontology-Based Similarity Between Text Documents on Manifold.- A Formalism of XML Restructuring Operations.- FTT Algorithm of Web Pageviews for Personalized Recommendation.- Social Network and RSS.- D-FOAF: Distributed Identity Management with Access Rights Delegation.- Community Focused Social Network Extraction.- Behavioral Analysis Based on Relations in Weblogs.- UniRSS: A New RSS Framework Supporting Dynamic Plug-In of RSS Extension Modules.- Ontology Integration and Interoperability 1.- Ontology-Based RBAC Specification for Interoperation in Distributed Environment.- Business Process Collaboration Using Semantic Interoperability: Review and Framework.- An Ontology Architecture for Integration of Ontologies.- Automatic Alignment of Ontology Eliminating the Probable Misalignments.- Ontology Integration and Interoperability 2.- Semantic Integration of Enterprise Information: Challenges and Basic Principles.- Application Integration Using Conceptual Spaces (CSpaces).- A New Evaluation Method for Ontology Alignment Measures.- Representing and Reasoning with Application Profiles Based on OWL and OWL/XDD.- Reasoning.- OWL-Full Reasoning from an Object Oriented Perspective.- Visualizing Defeasible Logic Rules for the Semantic Web.- A Reasoning Algorithm for pD*.- Triple Space Computing: Adding Semantics to Space-Based Computing.- Application 1.- Full-Automatic High-Level Concept Extraction from Images Using Ontologies and Semantic Inference Rules.- Dental Decision Making on Missing Tooth Represented in an Ontology and Rules.- Ontology Driven Visualisation of Maps with SVG - Technical Aspects.- Applying CommonKADS and Semantic Web Technologies to Ontology-Based E-Government Knowledge Systems.- A Semantics-Based Protocol for Business Process Transactions.- Information Search.- Fuzzy View-Based Semantic Search.- A Semantic Search Conceptual Model and Application in Security Access Control.- Document Filtering for Domain Ontology Based on Concept Preferences.- Database.- Qualitative Spatial Relation Database for Semantic Web.- Automatic Creation and Simplified Querying of Semantic Web Content: An Approach Based on Information-Extraction Ontologies.- HStar - A Semantic Repository for Large Scale OWL Documents.- Minerva: A Scalable OWL Ontology Storage and Inference System.- Semantic Web Services 1.- Exploring the Flexible Workflow Technology to Automate Service Composition.- Mediation Enabled Semantic Web Services Usage.- Toward Automatic Discovery and Invocation of Information-Providing Web Services.- Automatic Composition of Semantic Web Services - A Theorem Proof Approach.- Semantic Web Services 2.- A Semantic Rewriting Approach to Automatic Information Providing Web Service Composition.- Web Services Analysis: Making Use of Web Service Composition and Annotation.- WWW: WSMO, WSML, and WSMX in a Nutshell.- Automatic Generation of Service Ontology from UML Diagrams for Semantic Web Services.- A Composition Oriented and Graph-Based Service Search Method.- Ontology and Tool.- DODDLE-OWL: A Domain Ontology Construction Tool with OWL.- Knowledge Elicitation Plug-In for Protege: Card Sorting and Laddering.- Towards a Topical Ontology of Fraud.- Application 2.- Product Data Interoperability Based on Layered Reference Ontology.- Design of Semantically Interoperable Adverse Event Reporting Framework.- Protein Data Sources Management Using Semantics.- Semantic Web Modeling for Virtual Organization: A Case Study in Logistics.- A PSO-Based Web Document Query Optimization Algorithm.- Ontology and Theory.- Modular Ontologies - A Formal Investigation of Semantics and Expressivity.- A Pi-Calculus Based Ontology Change Management.- A Comprehensive Study of Inappropriate Hierarchy in WordNet.- Autonomous Ontology: Operations and Semantics OR Local Semantics with Semantic Binding on Foreign Entity.- Peer-to-Peer.- SemreX: A Semantic Peer-to-Peer System for Literature Documents Retrieval.- Personal Information Modeling in Semantic Web.- A Semantic Reputation Mechanism in P2P Semantic Web.- Client and Server Anonymity Preserving in P2P Networks.- Industrial Track 1.- A Map Ontology Driven Approach to Natural Language Traffic Information Processing and Services.- A Knowledge- and Workflow-Based System for Supporting Order Fulfillment Process in the Build-to-Order Supply Chains.- A Distributed IR Model Based on Semantic Web.- Experimental Study of Semantic Contents Mining on Intra-university Enterprise Contents Management System for Knowledge Sharing.- Industrial Track 2.- Semantic Autocompletion.- Ubiquitous Metadata Scouter - Ontology Brings Blogs Outside.- Networked Interactive Photo Annotation and Reminiscence Content Delivery.- Task-Oriented Mobile Service Recommendation Enhanced by a Situational Reasoning Engine.
121 citations
08 Dec 2008
TL;DR: This paper addresses the issue of identifying the concepts in an ontology, which best summarize what the ontology is about, and shows two versions of the algorithm, which have been evaluated against the results produced by human experts.
Abstract: In this paper we address the issue of identifying the concepts in an ontology, which best summarize what the ontology is about. Our approach combines a number of criteria, drawn from cognitive science, network topology, and lexical statistics. In the paper we show two versions of our algorithm, which have been evaluated against the results produced by human experts. We report that the latest version of the algorithm performs very well, exhibiting an excellent degree of correlation with the choices of the experts. While the generation of automatic methods for ontology summarization is an interesting research issue in itself, the work described here also provides a basis for novel approaches to a variety of ontology engineering tasks, including ontology matching, automatic classification, ontology modularization, and ontology evaluation.
120 citations
Proceedings Article•
06 Jan 2007TL;DR: This work presents a novel approach that allows similarities to be asymmetric while still using only information contained in the structure of the ontology, and shows that the new approach achieves better accuracy than existing techniques.
Abstract: Various approaches have been proposed to quantify the similarity between concepts in an ontology We present a novel approach that allows similarities to be asymmetric while still using only information contained in the structure of the ontology We show through experiments on the WordNet and GeneOntology that the new approach achieves better accuracy than existing techniques
120 citations
09 Apr 2007
TL;DR: This paper proposes a new representation of ontology-based data, called table per class, which consists in associating a table to each ontology class, where all property values of a class instance are represented in a same row.
Abstract: Recently, several approaches and systems were proposed to store in the same database data and the ontologies describing their meanings. We call these databases, ontology-based databases (OBDBs). Ontology-based data denotes those data that represent ontology individuals (i.e., instance of ontology classes). To speed up query execution on the top of these OBDBs, efficient representations of ontology-based data become a new challenge. Two main representation schemes have been proposed for ontology-based data: vertical and binary representations with a variant called hybrid. In these schemes, each instance is split into a number of tuples. In this paper, we propose a new representation of ontology-based data, called table per class. It consists in associating a table to each ontology class, where all property values of a class instance are represented in a same row. Columns of this table represent those properties of the ontology class that are associated with a value for at least one instance of this class. We present the architecture of our ontology-based databases and a comparison of the effectiveness of our representation scheme with the existing ones used in Semantic Web applications. Our benchmark involves three categories of queries: (1) targeted class queries, where users know the classes they are querying, (2) no targeted class queries, where users do not know the class(es) they are querying, and (3) update queries.
120 citations