User Intent Discovery Using Search Logs and Social Network Analysis
Wael K. Hanna, Aziza Saad Asem, M. B. Senouy · WSEAS Transactions on Computers archive · 2017
With the continuous growing of applications of internet and Web 2.0, users have the opportunity to publish data over the Web. Search engines face many difficulties to return search results whose rankings based on users’ intents. All search engines provide search log of the user by tracking their online searches through recording their queries and click information besides browsing history has been stored at the client side. Also, social networks provide a powerful tool for extracting the users’ interests from profile and activities of user’s different social networks. This paper presents a new proposed method of enabling personalized Web search for users based on their extracted interests and intents from search logs and composite social networks. This paper explores various extracted features and intents from previous resources. Then clustering the users’ extracted intents and use it to re-rank the web search results. The implementation and the evaluation of the proposed method were presented by improving the performance of the Web search engines