Query clustering using user logs
ACM Transactions on Information Systems (TOIS)
SimRank: a measure of structural-context similarity
Proceedings of the eighth ACM SIGKDD international conference on Knowledge discovery and data mining
Journal of the American Society for Information Science and Technology
Generating query substitutions
Proceedings of the 15th international conference on World Wide Web
Context-aware query suggestion by mining click-through and session data
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
Simrank++: query rewriting through link analysis of the click graph
Proceedings of the VLDB Endowment
The query-flow graph: model and applications
Proceedings of the 17th ACM conference on Information and knowledge management
Discovering search engine related queries using association rules
Journal of Web Engineering
Query recommendation using query logs in search engines
EDBT'04 Proceedings of the 2004 international conference on Current Trends in Database Technology
Query suggestions in the absence of query logs
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
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Generating similar queries for a query, named query suggestion, is an important technology for helping search engine users. Since query data is very diverse and sparse, it is still challenging to measure the similarity of each query pair. We propose a novel algorithm called QueryTrans, which can efficiently compute pairwise similarity scores between all queries with respect to the global structure of a query trace graph mined from search engine logs. Compared with previous query suggestion approaches, QueryTrans is robust for different queries and stable for different parameter settings. We also present the performance of QueryTrans on large scale query logs. Experiments on about 100,000 queries show: QueryTrans can efficiently computes almost 10 billion pairwise similarity scores within 15 minutes on a single computer; and its results are significantly better than all 4 recent approaches on query suggestion.