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Upper ontology

About: Upper ontology is a research topic. Over the lifetime, 9767 publications have been published within this topic receiving 220721 citations. The topic is also known as: top-level ontology & foundation ontology.


Papers
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Book ChapterDOI
29 May 2005
TL;DR: This paper presents an ontology which formalizes the main concepts which are used in an DILIGENT ontology engineering discussion and thus enables tracking arguments and allows for inconsistency detection, and enables the integration of manual, semi-automatic and automatic ontology creation approaches.
Abstract: A prerequisite to the success of the Semantic Web are shared ontologies which enable the seamless exchange of information between different parties. Engineering a shared ontology is a social process. Since its participants have slightly different views on the world, a harmonization effort requires discussing the resulting ontology. During the discussion, participants exchange arguments which may support or object to certain ontology engineering decisions. Experience from software engineering shows that tracking exchanged arguments can help users at a later stage to better understand the assumptions underlying the design decisions. Furthermore, as the constructed ontology becomes larger, ontology engineers might argue in a contradictory way without knowing so. In this paper we present an ontology which formalizes the main concepts which are used in an DILIGENT ontology engineering discussion and thus enables tracking arguments and allows for inconsistency detection. We provide an example which is drawn from experiments in an ontology engineering process to construct an ontology for knowledge management in our institute. Having constructed the ontology we also show how automated ontology learning algorithms could be taken as participants in the OE discussion. Hence, we enable the integration of manual, semi-automatic and automatic ontology creation approaches.

121 citations

Journal ArticleDOI
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

Book ChapterDOI
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 2007
TL;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


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Performance
Metrics
No. of papers in the topic in previous years
YearPapers
202343
2022155
20219
20205
20199
201838