A semantic complement to enhance electronic market

Authors:
Sharmin Moosavi;Mohammadali Nematbakhsh;Hadi Khosravi Farsani
Affiliations:
Computer Engineering Department, University of Isfahan, Hezarjerib.st, Isfahan, Iran;Computer Engineering Department, University of Isfahan, Hezarjerib.st, Isfahan, Iran;Computer Engineering Department, University of Isfahan, Hezarjerib.st, Isfahan, Iran
Venue:
Expert Systems with Applications: An International Journal
Year:
2009

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Abstract

Consumers prefer to purchase bundled and related products to use them together to perform a task or satisfy a need. In this paper, we propose a complementary association for bundling products to enhance promotions, recommendations and selling strategies in marketplaces such as combinatorial auction. We propose an ontology based model and define a Need association to determine complement of product classes. Using this type of association, we develop a mathematical model to relatively measure complementary degree of classes and the latest purchased products to recommend Top-N products. We experiment this approach with a recommender system utilizing complementary products. Experimental results on the dataset of Building Equipment Company show superiority in terms of performance and precision.