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Research on topic maps-based ontology information retrieval model

Paper, was published by Qing-mao Li, Xing-jiang Yang, Xiang-bing Zhou, and Hong-jiang Ma at 2010-01-01

This paper shows that the topic map-based ontology information retrieval model performs better than the traditional model.

External Link: more information


Ontology is normative, explicit and reusable when defining the domain concept, so it can be combined with topic maps to organize information resource for semantic navigation. An information retrieval model based on topic maps and ontology was proposed and defined formally. Firstly it specified a domain of tourism document. Secondly it defined the ontology and topic maps of tourism document in order to normalize query that user directly input in natural language, and identified the user’s real meaning of search. Thus, it can expand user-semantic search. Therefore analyzed the effect of the ontology was analyzed, and a valuable function of semantic navigation and sorting the retrieval result correlated with user’s query was shown. Finally, the experimental result shows that the topic map-based ontology information retrieval model can perform better than the traditional model.

Please note: Full article is in Chinese!

Authors

Qing-mao Li

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Qing-mao is author of Research on topic maps-based.. and Research on Topic Maps-based.. .

Xing-jiang Yang

No contact information available. 

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Xing-jiang is author of Research on topic maps-based.. .

Xiang-bing Zhou

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Xiang-bing is author of Research on topic maps-based.. , Ontology-oriented Navigation.. , Semantics Web service.. , and A Service Clustering.. .

Hong-jiang Ma

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Hong-jiang is author of Research on topic maps-based.. and Semantics Web service.. .

 

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