TY - JOUR
T1 - Recommendation of e-commerce sites by matching category-based buyer query and product e-catalogs
AU - Kwon, Ick Hyun
AU - Kim, Chang Ouk
AU - Kim, Kyung Pil
AU - Kwak, Choonjong
PY - 2008/4
Y1 - 2008/4
N2 - In this paper, an e-commerce site recommendation system that integrates multiple e-commerce sites is proposed. This system provides the users with a unified portal through which the users can search individual suppliers' product categories efficiently. The core part of the system is an intelligent product meta-search engine that has the following functions: (1) it provides category-based query, with which a buyer can describe his or her product search intention using superclass/subclass relationship, (2) by using WordNet, the buyer's query is semantically extended in order to increase product search accuracy, and (3) the meta-search engine decides a recommended priority of the suppliers by matching the buyer's query with the suppliers' product categories and computing a semantic relevancy measure. Experiments show that the performance of the meta-search is better than those of general keyword-based search and category-based search.
AB - In this paper, an e-commerce site recommendation system that integrates multiple e-commerce sites is proposed. This system provides the users with a unified portal through which the users can search individual suppliers' product categories efficiently. The core part of the system is an intelligent product meta-search engine that has the following functions: (1) it provides category-based query, with which a buyer can describe his or her product search intention using superclass/subclass relationship, (2) by using WordNet, the buyer's query is semantically extended in order to increase product search accuracy, and (3) the meta-search engine decides a recommended priority of the suppliers by matching the buyer's query with the suppliers' product categories and computing a semantic relevancy measure. Experiments show that the performance of the meta-search is better than those of general keyword-based search and category-based search.
UR - http://www.scopus.com/inward/record.url?scp=39749112018&partnerID=8YFLogxK
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U2 - 10.1016/j.compind.2007.10.002
DO - 10.1016/j.compind.2007.10.002
M3 - Article
AN - SCOPUS:39749112018
VL - 59
SP - 380
EP - 394
JO - Computers in Industry
JF - Computers in Industry
SN - 0166-3615
IS - 4
ER -