Description

ABSTRACT:

We propose a personalized mobile search engine (PMSE) that captures the users’ preferences in

the form of concepts by mining their click through data. Due to the importance of location

information in mobile search, PMSE classifies these concepts into content concepts and location

concepts. In addition, users’ locations (positioned by GPS) are used to supplement the location

concepts in PMSE. The user preferences are organized in an ontology-based, multifacet user

profile, which are used to adapt a personalized ranking function for rank adaptation of future

search results. To characterize the diversity of the concepts associated with a query and their

relevances to the user’s need, four entropies are introduced to balance the weights between the

content and location facets. Based on the client-server model, we also present a detailed

architecture and design for implementation of PMSE.