SIGIR '92 Proceedings of the 15th annual international ACM SIGIR conference on Research and development in information retrieval
Mining association rules between sets of items in large databases
SIGMOD '93 Proceedings of the 1993 ACM SIGMOD international conference on Management of data
An effective hash-based algorithm for mining association rules
SIGMOD '95 Proceedings of the 1995 ACM SIGMOD international conference on Management of data
Query expansion using local and global document analysis
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Fast discovery of association rules
Advances in knowledge discovery and data mining
Improving automatic query expansion
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Managing gigabytes (2nd ed.): compressing and indexing documents and images
Improving the effectiveness of information retrieval with local context analysis
ACM Transactions on Information Systems (TOIS)
Journal of the American Society for Information Science
Generating non-redundant association rules
Proceedings of the sixth ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 6th international conference on Intelligent user interfaces
Using quantitative information for efficient association rule generation
ACM SIGMOD Record
Clustering user queries of a search engine
Proceedings of the 10th international conference on World Wide Web
Probabilistic query expansion using query logs
Proceedings of the 11th international conference on World Wide Web
Modern Information Retrieval
Efficient Adaptive-Support Association Rule Mining for Recommender Systems
Data Mining and Knowledge Discovery
Local versus global link information in the Web
ACM Transactions on Information Systems (TOIS)
Fast Algorithms for Mining Association Rules in Large Databases
VLDB '94 Proceedings of the 20th International Conference on Very Large Data Bases
An Efficient Algorithm for Mining Association Rules in Large Databases
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Journal of the American Society for Information Science and Technology
The SMART Retrieval System—Experiments in Automatic Document Processing
The SMART Retrieval System—Experiments in Automatic Document Processing
Concept-based interactive query expansion
Proceedings of the 14th ACM international conference on Information and knowledge management
Recommending questions using the mdl-based tree cut model
Proceedings of the 17th international conference on World Wide Web
Discovering co-located queries in geographic search logs
Proceedings of the first international workshop on Location and the web
Proceedings of the 14th ACM SIGKDD international conference on Knowledge discovery and data mining
QueryTrans: Finding Similar Queries Based on Query Trace Graph
WI-IAT '09 Proceedings of the 2009 IEEE/WIC/ACM International Joint Conference on Web Intelligence and Intelligent Agent Technology - Volume 01
Evaluating Google queries based on language preferences
Journal of Information Science
Moving towards adaptive search in digital libraries
NLP4DL'09/AT4DL'09 Proceedings of the 2009 international conference on Advanced language technologies for digital libraries
Learning adaptive domain models from click data to bootstrap interactive web search
ECIR'12 Proceedings of the 34th European conference on Advances in Information Retrieval
New assessment criteria for query suggestion
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Learning to rank query suggestions for adhoc and diversity search
Information Retrieval
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This work presents a method for online generation of query related suggestions for a Web search engine. The method uses association rules to extract related queries from the log of sbumitted queries to the search engine. Experimental results were performed on a real log containing more than 2.3 million queries submitted to a commercial search engine. For the top 5 related terms our method presented correct suggestions in 90.5% of the time. Using queries randomly selected from a log we obtained 93.45% of correct suggestions. A study of the user behavior showed that in 92.23% of the clicks on suggestions, users found useful information. The same approach can be used to provide terms to the classic problem of query expansion. For instance, the average precision of the answers of the Google search engine was improved by 23.16% using our aproach as a query expansion method.