Using folksonomies for building user interest profile

This work exploits folksonomy for building User Interest Profile (UIP) based on user's search history. UIP is an indispensable source of knowledge which can be exploited by intelligent systems for query recommendation, personalized search, and web search result ranking etc. A UIP consist of a clustered list of concepts and their weights. We show how to design, implement, and visualize such a system, in practice, which aids in finding interesting relationships between concepts and detect outliers, if any. The experiment reveals that UIP not only captures user interests but also its context and results are very promising.