Understanding user's query intent with wikipedia

Understanding the intent behind a user's query can help search engine to automatically route the query to some corresponding vertical search engines to obtain particularly relevant contents, thus, greatly improving user satisfaction. There are three major challenges to the query intent classification problem: (1) Intent representation; (2) Domain coverage and (3) Semantic interpretation. Current approaches to predict the user's intent mainly utilize machine learning techniques. However, it is difficult and often requires many human efforts to meet all these challenges by the statistical machine learning approaches. In this paper, we propose a general methodology to the problem of query intent classification. With very little human effort, our method can discover large quantities of intent concepts by leveraging Wikipedia, one of the best human knowledge base. The Wikipedia concepts are used as the intent representation space, thus, each intent domain is represented as a set ...

• Type: Conference
• Year: 2009
• Where: WWW
• Authors: Jian Hu, Gang Wang, Frederick H. Lochovsky, Jian-Tao Sun, Zheng Chen
• Keywords: Intent Representation Space, Internet Technology, Query Intent Classification, Seed Intent Queries, WWW 2009