Towards Automatic Generation of Query Taxonomy: A Hierarchical Query Clustering Approach

Previous works on automatic query clustering most generate a flat, un-nested partition of query terms. In this work, we are pursuing to organize query terms into a hierarchical structure and construct a query taxonomy in an automatic way. The proposed approach is designed based on a hierarchical agglomerative clustering algorithm to hierarchically group similar queries and generate the cluster hierarchies by a novel cluster partition technique. The search processes of real-world search engines are combined to obtain highly ranked Web documents as the feature source for each query term. Preliminary experiments show that the proposed approach is effective to obtain thesaurus information for query terms, and is also feasible to construct a query taxonomy which provides a basis for in-depth analysis of users’ search interests and domain-specific vocabulary on a larger scale.