A Framework for an Ontology-based E-commerce Product Information Retrieval System

With the rapid development of e-commerce, online shopping has become an important part in people's lives, in order to support the smooth development of e-commerce activities, how to provide users with an efficient and practical product information search method has become an urgent and critical problem. This paper presents a framework for an ontology-based e-commerce product information retrieval system and proposes an ontology-based adaptation of the classical Vector Space Model with the consideration of the weight of product attribute. A computer and components related ontology has been built, which is adopted to annotate the html documents and construct concept vectors of the documents. Then the system test is done and the experimental result indicates that our proposal is better than the traditional keywords based search.

[1]  Thomas R. Gruber,et al.  A translation approach to portable ontology specifications , 1993, Knowl. Acquis..

[2]  Yelena Yesha,et al.  Strategic directions in electronic commerce and digital libraries: towards a digital agora , 1996, CSUR.

[3]  Susan T. Dumais,et al.  Improving the retrieval of information from external sources , 1991 .

[4]  Óscar Corcho,et al.  A Semantic Portal for the International Affairs Sector , 2004, EKAW.

[5]  Yiyu Yao,et al.  Conceptual Query Expansion , 2005, AWIC.

[6]  Pablo Castells,et al.  Semantic Web Technologies for Economic and Financial Information Management , 2004, ESWS.

[7]  Kilian Stoffel,et al.  knOWLer - Ontological Support for Information Retrieval Systems , 2003 .

[8]  Jesús Contreras,et al.  Neptuno: Semantic Web Technologies for a Digital Newspaper Archive , 2004, ESWS.

[9]  Nicola Guarino,et al.  OntoSeek: content-based access to the Web , 1999, IEEE Intell. Syst..

[10]  Bijan Parsia,et al.  Ontology-Enabled Pervasive Computing Applications , 2003, IEEE Intell. Syst..

[11]  Zhang Wei-ming,et al.  Ontology-based information retrieval model for the semantic Web , 2005, 2005 IEEE International Conference on e-Technology, e-Commerce and e-Service.

[12]  Enrico Motta,et al.  SemSearch: A Search Engine for the Semantic Web , 2006, EKAW.

[13]  Timothy W. Finin,et al.  Enabling Technology for Knowledge Sharing , 1991, AI Mag..

[14]  Jun-feng Song,et al.  Ontology-Based Information Retrieval Model for the Semantic Web , 2005, EEE.

[15]  Atanas Kiryakov,et al.  KIM – a semantic platform for information extraction and retrieval , 2004, Natural Language Engineering.

[16]  Ramanathan V. Guha,et al.  Semantic search , 2003, WWW '03.

[17]  Robert Richards,et al.  Document Object Model (DOM) , 2006 .

[18]  N. F. Noy,et al.  Ontology Development 101: A Guide to Creating Your First Ontology , 2001 .

[19]  Wu Cheng.  AN INFORMATION RETRIEVAL SERVER BASED ON ONTOLOGY AND MULTI-AGENT , 2001 .

[20]  Huajun Chen,et al.  The Semantic Web , 2011, Lecture Notes in Computer Science.

[21]  E. Prud hommeaux,et al.  SPARQL query language for RDF , 2011 .

[22]  Michael McGill,et al.  Introduction to Modern Information Retrieval , 1983 .

[23]  Daniel Schwabe,et al.  A hybrid approach for searching in the semantic web , 2004, WWW '04.

[24]  Yuh-Min Chen,et al.  A semantic-based approach to content abstraction and annotation for content management , 2009, Expert Syst. Appl..

[25]  Pablo Castells,et al.  An Adaptation of the Vector-Space Model for Ontology-Based Information Retrieval , 2007, IEEE Transactions on Knowledge and Data Engineering.

[26]  David Carmel,et al.  Topic Distillation with Knowledge Agents , 2002, TREC.