Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
Constraint-Based Rule Mining in Large, Dense Databases
ICDE '99 Proceedings of the 15th International Conference on Data Engineering
Mining search engine query logs for query recommendation
Proceedings of the 15th international conference on World Wide Web
Query recommendation using query logs in search engines
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
| Hi-index | 0.01 |
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 user's 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.