Identification of Web Query Intent Based on Query Text and Web Knowledge

In this paper, we propose a novel approach to identifying user intents of search engine queries. Specifically, we recast it as a classification problem, in which four types of features are adopted. The classification features are based on deep linguistic analysis of queries as well as search engine feedbacks. We evaluate the method with the real web query data. The results show that about 88% of the test queries can be correctly identified with the classification framework via combining all the 4 types of features.