3rd International Conference on Network and System Security, Surfers Paradise, Australia, 19 - 21 October 2009, pp.560-564
We introduce a method to help people to refine their search queries based on other people's similar queries. We compared two different methods of collaborative filtering on search logs of a popular e-commerce site to do query expansion. In item-based method, by identifying similarities between different items, and in user-based method, by identifying similarities between different users, we compute recommendations for users. The experimental results show that item-based query expansion method provides better performance than the user-based method. While the user-based method improved the system performance 20%, the item-based method provided success of 73%. Also, item-based method recommended better expansion terms than the user-based method, which is important in helping web users to easily access information needs by formulating qualified queries. This document is a comparison of these two methods, and their effects on system performance.