Matching relevance features with ontological concepts


Autoria(s): Shen, Yan; Li, Yuefeng; Xu, Yue; Tao, Xiaohui
Contribuinte(s)

Boissier, Olivier

Benatallah, Boualem

Data(s)

04/12/2012

Resumo

In order to comprehend user information needs by concepts, this paper introduces a novel method to match relevance features with ontological concepts. The method first discovers relevance features from user local instances. Then, a concept matching approach is developed for matching these features to accurate concepts in a global knowledge base. This approach is significant for the transition of informative descriptor and conceptional descriptor. The proposed method is elaborately evaluated by comparing against three information gathering baseline models. The experimental results shows the matching approach is successful and achieves a series of remarkable improvements on search effectiveness.

Identificador

http://eprints.qut.edu.au/58388/

Publicador

IEEE Computer Society Conference Publishing Services (CPS)

Relação

http://www.fst.umac.mo/wic2012/IAT/?category=participants&node=5

Shen, Yan, Li, Yuefeng, Xu, Yue, & Tao, Xiaohui (2012) Matching relevance features with ontological concepts. In Boissier, Olivier & Benatallah, Boualem (Eds.) The 2012 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology Workshops, IEEE Computer Society Conference Publishing Services (CPS), Macau, China, pp. 190-194.

Direitos

Copyright 2012 The Institute of Electrical and Electronics Engineers, Inc.

Fonte

School of Electrical Engineering & Computer Science; Science & Engineering Faculty

Palavras-Chave #080109 Pattern Recognition and Data Mining #Relevance Feature #Concept Matching #Ontology learning #Local Instance #Global Knowledge Base
Tipo

Conference Paper