Personalized web search using emotional features

Abstract

Re-ranking and re-retrieval of search results are useful techniques for satisfying users' search intentions, since current search engines cannot always return user-desired pages at the top ranks. In this paper, we propose a system for personalized Web search considering users' emotional aspects. Given a query topic, the system presents the major emotion tendency on this topic that search results returned from search engines are reflecting. The system also enables users to specify the polarities and strengths of their emotions (e.g., happy or sad, glad or angry, peaceful or strained) on this topic and offers a re-ranking list of initial search results based on the similarity of emotions. Particularly, the system can automatically obtain Web pages with minor emotion tendency on the query topic by extracting sub-queries with opposite emotions and conducting a re-retrieval. Experimental evaluations show the re-ranking and the re-retrieval achieve encouraging search results in comparison with initial search results. © 2013 IFIP International Federation for Information Processing.