Search Query Expansion using Genetic Algorithm?based Clustering
D. Indumathi · The Smart Computing Review · 2013
The World Wide Web has become a resource pool for people seeking information. Current Web search engines try to deliver relevant information to users, but due to both exponential growth of information and imprecise queries, search engines cannot meet users’ information requirements. Users have to reframe queries until they get the desired information. To improve users’ search experience, some search engines provide query suggestions that are semantically related to a particular query. These systems provide the same suggestions to the same queries without considering the personal interest of the user. This paper presents an approach to provide personalized query suggestions based on a genetic algorithm?based clustering technique. This improves retrieval effectiveness and relevancy by expanding the query with additional words. Unlike existing methods, this technique provides personalized query suggestions for each individual user according to that user’s conceptual needs. The main objective of this work is to improve retrieval of information by expanding the user’s query based on the user’s domain of interest.