Search engine queries are often too vague to achieve relevant results. This paper presents an intelligent query approach that can distinguish vague queries and organize the related queries of each vague query into a concept hierarchy. Through the concept hierarchy, users can quickly find proper queries for their informational needs. The TECH (term concept hunting) is proposed, based on the small world of human languages. TECH utilizes both the community detection algorithms in the physical field and IR techniques in the computer science field to generate an extensible framework. Experimental results show that compared with the traditional listing query suggestion manner, users prefer the intelligent query suggestion. TECH can effectively distinguish vague queries and significantly outperforms the other three state-of-the-art hierarchical building systems statistically.