An Ontology-Based Product Recommender System for B2B Marketplaces

  • Authors:
  • Taehee Lee;Jonghoon Chun;Junho Shim;Sang-Goo Lee

  • Affiliations:
  • Seoul National University;Department of Computer Engineering, Myongji University, Korea;Seoul National University, Korea;School of Computer Science and Engineering, Seoul National University, Korea

  • Venue:
  • International Journal of Electronic Commerce
  • Year:
  • 2006

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Abstract

An ontology-based product-recommender system can help catalog administrators in B2B marketplaces maintain up-to-date product databases by acquiring mapping information between the new product data and existing data. The proposed approach is keyword-based and independent of the underlying physical structure of product ontology. With a Bayesian belief network as its basis, the ranking algorithm utilizes semantics embedded within relationships defined in ontology to probabilistically determine the ranking scores. The methodology is implemented on a practical ontology system powerful enough to assist users in B2B marketplaces. Its effectiveness is demonstrated in comparison to the conventional search engines.