Mining search engine query logs for query recommendation

ABSTRACT

This paper presents a simple and intuitive method for mining search engine query logs to get fast query recommendations on a large scale industrial strength search engine. In order to get a more comprehensive solution, we combine two methods together. On the one hand, we study and model search engine users' sequential search behavior, and interpret this consecutive search behavior as client-side query refinement, that should form the basis for the search engine's own query refinement process. On the other hand, we combine this method with a traditional content based similarity method to compensate for the high sparsity of real query log data, and more specifically, the shortness of most query sessions. To evaluate our method, we use one hundred day worth query logs from SINA' search engine to do off-line mining. Then we analyze three independent editors evaluations on a query test set. Based on their judgement, our method was found to be effective for finding related queries, despite its simplicity. In addition to the subjective editors' rating, we also perform tests based on actual anonymous user search sessions.

REFERENCES

• 1: R. Baeza-Yates, C. Hurtado, and M. Mendoza. Query recommendation using query logs in search engines. In International Workshop on Clustering Information over the Web (ClustWeb, in conjunction with EDBT), Creete, Greece, March (to apper in LNCS)., 2004.
• 2: Doug Beeferman , Adam Berger, Agglomerative clustering of a search engine query log, Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining, p.407-416, August 20-23, 2000, Boston, Massachusetts, United States [doi>10.1145/347090.347176]
• 3: Query clustering using user logs, ACM Transactions on Information Systems (TOIS), v.20 n.1, p.59-81, January 2002 [doi>10.1145/503104.503108]

INDEX TERMS

Primary Classification:
  H. Information Systems
  H.2 DATABASE MANAGEMENT
      H.2.8 Database applications
          Subjects: Data mining

Additional Classification:
  H. Information Systems
  H.3 INFORMATION STORAGE AND RETRIEVAL
      H.3.3 Information Search and Retrieval
          Subjects: Query formulation

Keywords:
mining, query logs, recommendation, session