A survey on retrieving Contextual User Profiles from Search Engine Repository
Jella Santhosh · 2012
Personalized search is an important research area that aims to resolve the ambiguity of query terms. Therefore a Personalized Search engine return the most appropriate search results related to users interest. For example, a query “apple” a farmer would be interested in the apple fruits plants, farm etc. a technician would be interested in apple OS, Mac, Macintosh where as a gadget freak would be interested in latest apple products like ipad, iphone, iPod etc. Here we focus on search engine personalization and develop several concept-based user profiling methods that are based on both positive and negative preferences. We evaluate the proposed methods against our proposed personalized query clustering method. Experimental results show that profiles which capture and utilize both of the user’s positive and negative preferences perform the best. An important result from the experiments is that profiles with negative preferences can increase the separation between similar and dissimilar queries. The separation provides a clear threshold for an agglomerative clustering algorithm to terminate and improve the overall quality of the resulting query clusters.