Personalized Search Engine using Social Networking Activity

Abstract

The main objective of this research work is to obtain a personalized search result required by the user, by creating user profile based on social networking activity. The user profile is actually constructed by pages liked by the individual user in Facebook on their respective user account. According to the constructed user profile the results are re-ranked and the personalised search results are obtained. Lingo- a novel algorithm is used for clustering the data. The search results are retrieved to user using Carrot2 API search engine. In the past, personalized search engines acquired data from surfing history implicitly or explicitly by machine learning whereas this work acquires data implicitly through user likes and also explicitly through user defined categories . The Facebook likes are given by each user only on their personal interest. Thus, these data play a vital in providing accurate search results to each user and provide exact search results as per the user interest. Keywords: Information Retrieval, Personalization, Search Engine, Social Network and Web Search