Java, Oracle, Big data, IR
Title of Thesis
Semantic query suggestion using Twitter Entities
Description of Thesis
There are many web information management methods and techniques that help search engines and news services to provide useful suggestions with respect to queries, thus facilitating the users’ search. However, the penetration of microblogging services in our daily life demands to also consider the social sphere as far as query suggestion is concerned. Towards this direction, an algorithmic approach capable of creating a dynamic query suggestion set, which consists of the most viral and trendy Twitter Entities (that is hashtags, user mentions and URLs) with respect to a user’s query. This method based on a social network derived by related trendy entities that become viral in Twitter worldwide.