Semantic Web Search System Founded on Case-Based Reasoning and Ontology Learning

With the continuous growth of data volume on the Web, the search for information has become a challenging task. Ontologies are used to improve the accuracy of information retrieval from the web by incorporating a degree of semantic analysis during the search. However, manual ontology building is time consuming. An automatic approach may aid to solve this problem by analyzing implicitly available knowledge such as the users’ search feedback. In this context, we propose a semantic web search system founded on Case-Based-Reasoning (CBR) and ontology learning that aims to enrich automatically the ontologies by using previous search queries performed by the user. Some experiments and results obtained with the proposed system are also presented, which show an improvement on the precision of the Web search and ontology enrichment.

[1]  Gerard Salton,et al.  Term-Weighting Approaches in Automatic Text Retrieval , 1988, Inf. Process. Manag..

[2]  Ian D. Watson,et al.  Case-based reasoning is a methodology not a technology , 1999, Knowl. Based Syst..

[3]  Daniel E. Rose,et al.  Understanding user goals in web search , 2004, WWW '04.

[4]  Hajer Baazaoui Zghal,et al.  A Model-Driven Approach of Ontological Components for On-line Semantic Web Information Retrieval , 2007, J. Web Eng..

[5]  Marti A. Hearst.  Automated Discovery of WordNet Relations , 2004 .

[6]  George A. Miller,et al.  Introduction to WordNet: An On-line Lexical Database , 1990 .

[7]  Eneko Agirre,et al.  Publicly Available Topic Signatures for all WordNet Nominal Senses , 2004, LREC.

[8]  Ian Horrocks,et al.  OIL in a Nutshell , 2000, EKAW.

[9]  Geoffrey C. Fox,et al.  A Web based conversational case-based recommender system for ontology aided metadata discovery , 2004, Fifth IEEE/ACM International Workshop on Grid Computing.

[10]  Eero Hyvönen,et al.  Combining Case-Based Reasoning and Semantic Indexing in a Question-Answer Service , 2006 .

[11]  Norbert Gronau,et al.  Architecture-Based Integration of CBR-Components into KM-Systems , 2002, German Workshop on Experience Management.

[12]  Steffen Staab,et al.  Ontology-based text clustering , 2001, IJCAI 2001.

[13]  Guishi Deng,et al.  The research of applying domain ontology to case-based reasoning system , 2005, Proceedings of ICSSSM '05. 2005 International Conference on Services Systems and Services Management, 2005..

[14]  Henda Hajjami Ben Ghézala,et al.  Enhancing semantic search using case-based modular ontology , 2010, SAC '10.

[15]  Steffen Staab,et al.  Handbook on Ontologies in Information Systems , 2003 .

[16]  Edward A. Fox,et al.  Research Contributions , 2014 .

[17]  Suresh Manandhar,et al.  An Unsupervised Method for General Named Entity Recognition and Automated Concept Discovery , 2004 .

[18]  David Faure,et al.  First experiences of using semantic knowledge learned by ASIUM for information extraction task using INTEX , 2000, ECAI Workshop on Ontology Learning.

[19]  Edwina L. Rissland,et al.  Using CBR to Drive IR , 1995, IJCAI.

[20]  Li Guan-yu,et al.  Design and Realization of Case-Based Ontology Reasoning , 2008, 2008 4th International Conference on Wireless Communications, Networking and Mobile Computing.

[21]  David Sánchez,et al.  Learning non-taxonomic relationships from web documents for domain ontology construction , 2008, Data Knowl. Eng..

[22]  Agnar Aamodt,et al.  Case-Based Reasoning: Foundational Issues, Methodological Variations, and System Approaches , 1994, AI Commun..

[23]  N. Guarino,et al.  Formal Ontology in Information Systems : Proceedings of the First International Conference(FOIS'98), June 6-8, Trento, Italy , 1998 .

[24]  Ralph Bergmann,et al.  On the Relations between Structural Case-based Reasoning and Ontologz-based Knowledge Management , 2003, Wissensmanagement.