Obtaining Personalized and Accurate Query Suggestion by Using Agglomerative Clustering Algorithm and P-QC Method

Personalized search is the important research area and its main aim is to resolve the ambiguity of the query terms issued by the user. Most of the queries supplied by the user to search engine tends to be short and ambiguous, so they are unable to express the user’s actual needs. To overcome this problem, we are creating user profiles to capture the user’s personal preference and in this way we can identify the actual goal of the input query. In this paper, agglomerative clustering algorithm is used to find the queries that are close to each other conceptually. We are considering relationship between users, queries and concepts to obtain accurate and more personalized query suggestions for the user. By applying our approach we are getting better precision and recall values when compared with previous query clustering methods. KeywordsSearch Engine, Personalization, Agglomerative Clustering, Click Through, WebSnippets.