Query expansion for effective retrieval from microblog

Twitter is most popular microblogging site. It provides us with real time data information. In this research paper we explain techniques for retrieving related information from twitter data according to user/people query. Aim of this method is finding real world and relevant information according to the query or interest profile of user. For extracting most relevant data used query expansion techniques. For expanding query we used word2vec model. Twitter has a large amount of information of any event. In the work presented here, the retrieval model finds most important data and gives the final ranking score to that information according user expanded interest profile.