Semantic Social Searching-An Ontology Based Approach

Nowadays, people rely on search engines for retrieving information. However, by submitting a query to traditional web search engines they get bundle of information at just one place. On the other hand when people wants to get expert opinion, they first try to approach their friends, families, and colleagues rather than a search engine because of the high level of intimacy trust. The recent and rapid rise of online social networking sites has made it possible to do it on a large scale. By keeping this in view many social searching tools are developed to facilitate the user to get the information from multiple social networking sites such as Google Social search, Social mention etc. These tool search information using keyword-based matching criteria, which makes it harder for normal user to find his/her desired information from the huge amount of retrieved data. This research work is intended to provide a social searching framework so that users can get the desired result easily. The proposed framework will first analyze the query semantically and filter out the irrelevant results and then results are ordered according to the user as well as post ranks. For that a ranking function will be devised that will compute users and posts ranking. As a result, user experience of performing social search will be improved.