An Ontology-Based Product Recommender System for B2B Marketplaces

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 st...

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Bibliographic Details
Published in:International journal of electronic commerce 2006-12, Vol.11 (2), p.125-155
Main Authors: Lee, Taehee, Chun, Jonghoon, Shim, Junho, Lee, Sang-goo
Format: Article
Language:English
Subjects:
B2B marketplaces
Bayesian belief network
Belief networks
Business to business
Business to business commerce
Cataloging
Domain ontologies
Effectiveness studies
Electronic commerce
keyword search
Keywords
Online searching
Ontology
OWL
Product information
product ontology
Product orientation
recommender system
Recommender systems
Search engines
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Summary: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.
ISSN:1086-4415
1557-9301
DOI:10.2753/JEC1086-4415110206