Sanjay Pundlkrao Ghatare

Mining product intention rules from transaction logs of an ecommerce portal

In this paper, we address the following problem: In the context of an ecommerce portal with product based inventory, predict the product p the user is interested, when he/she issues a query q. A viable solution to the above problem is necessary for e-commerce portals to a:) increase the relevance of their search results and b:) provide high quality recommendations. Higher quality search results and recommendations foster user purchases and thereby leading to increased revenue. We propose a rule based framework that maps a users query to a product. We propose a systematic search strategy that mines product intention rules from transaction logs of an ecommerce site. We validate the efficacy of the rules by running extensive experiments. Our results show that our approach produces product intention rules with high accuracy and coverage.