-- 作者:skinner
-- 发布时间:12/29/2006 10:25:00 PM
-- [B]奉献两篇文章,以表谢意[/B]
1. 2. 1.Ontology-based semantic matchmaking approach Gao Shu, Omer F. Rana, Nick J. Avis, Chen Dingfang Abstract:As a greater number of Web Services are made available, support for service discovery mechanisms become essential. Services can have quite different Quality of Service characteristics (such as their response time when given a particular set of data). A service requestor therefore requires more sophisticated approaches to find a service that meets a particular behavior, because supporting matching between a service request and properties is not straightforward. Matchmaking plays a vital role in this discovery process. We propose a novel matchmaking algorithm to effectively compute the semantic distance of concepts in an ontology. It is based on description logic formalization and reasoning, extends simple subsumption matching found in other approaches and allows match ranking. We have implemented the proposed approach and used the developed prototype in the context of service discovery in the visualization domain. 2006 Elsevier Ltd. All rights reserved. 2.Ontology based text indexing and querying for the semantic web Jacob Ko¨ hler , Stephan Philippi , Michael Spechtc, Alexander Ru¨egg Abstract:This publication shows how the gap between theHTMLbased internet and the RDF based vision of the semantic web might be bridged, by linking words in texts to concepts of ontologies. Most current search engines use indexes that are built at the syntactical level and return hits based on simple string comparisons. However, the indexes do not contain synonyms, cannot differentiate between homonyms (‘mouse’ as a pointing vs. ‘mouse’ as an animal) and users receive different search results when they use different conjugation forms of the same word. In this publication, we present a system that uses ontologies and Natural Language Processing techniques to index texts, and thus supports word sense disambiguation and the retrieval of texts that contain equivalent words, by indexing them to concepts of ontologies. For this purpose, we developed fully automated methods for mapping equivalent concepts of imported RDF ontologies (for this prototype WordNet, SUMO and OpenCyc). These methods will thus allow the seamless integration of domain specific ontologies for concept based information retrieval in different domains. To demonstrate the practical workability of this approach, a set of web pages that contain synonyms and homonyms were indexed and can be queried via a search engine like query frontend. However, the ontology based indexing approach can also be used for other data mining applications such text clustering, relation mining and for searching free text fields in biological databases. The ontology alignment methods and some of the text mining principles described in this publication are now incorporated into the ONDEX system
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