Personalized search based on micro-blogging social networks

In todays life, everybody who knows the Internet is familiar with web-based search engines and micro-blogging social networks. People from all over the world are using search engines as well as sending a huge amount of text messages to micro-blogging social networks in the daily life. This work addresses the problem of using micro-blogging social networks to personalize search engine results. We introduce a framework which combines the similarity of results fetched from a non-personalized search engine and the users's interests extracted from the micro-blogging social networks. We used the Twitter social network as the experimental domain to test the performance of proposed algorithms and evaluate the results by applying the algorithms on some of the well-known users who we know their interests.