Article

Using Association Rules to Discover Search Engines Related Queries

Authors:

Bruno M. Fonseca,

Paulo B. Golgher,

Edleno S. de Moura,

Nivio ZivianiAuthors Info & Claims

LA-WEB '03: Proceedings of the First Conference on Latin American Web Congress

Page 66

Published: 10 November 2003 Publication History

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Abstract

This work presents a method for automatic generate suggestions of related queries submitted toWeb search engines. The method extracts information from the log of past submitted queries to search engines using algorithms for mining association rules. Experimental results were performed on a log containing more than 2.3 million queries submitted to a commercial searching engine giving correct suggestions in 90.5% of the top 5 suggestions presented for common queries extracted from a real log.

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Jiang JWang WCuzzocrea AAllan JPaton NSrivastava DAgrawal RBroder AZaki MCandan SLabrinidis ASchuster AWang H(2018)RINProceedings of the 27th ACM International Conference on Information and Knowledge Management10.1145/3269206.3271808(197-206)Online publication date: 17-Oct-2018
https://dl.acm.org/doi/10.1145/3269206.3271808
Adhikari BSondhi PZhang WSharma MPrakash BChampin PGandon FMédini LLalmas MIpeirotis P(2018)Mining E-Commerce Query Relations using Customer Interaction NetworksProceedings of the 2018 World Wide Web Conference10.1145/3178876.3186174(1805-1814)Online publication date: 10-Apr-2018
https://dl.acm.org/doi/10.1145/3178876.3186174
Wang JHuang JWu DGuo JLan Y(2016)An incremental model on search engine query recommendationNeurocomputing10.1016/j.neucom.2016.09.003218:C(423-431)Online publication date: 19-Dec-2016
https://dl.acm.org/doi/10.1016/j.neucom.2016.09.003
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Index Terms

Using Association Rules to Discover Search Engines Related Queries
1. Information systems
2. Theory of computation
  1. Theory and algorithms for application domains
    1. Database theory
      1. Database query processing and optimization (theory)

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Published In

LA-WEB '03: Proceedings of the First Conference on Latin American Web Congress

November 2003

ISBN:0769520588

Publisher

IEEE Computer Society

United States

Publication History

Published: 10 November 2003

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Jiang JWang WCuzzocrea AAllan JPaton NSrivastava DAgrawal RBroder AZaki MCandan SLabrinidis ASchuster AWang H(2018)RINProceedings of the 27th ACM International Conference on Information and Knowledge Management10.1145/3269206.3271808(197-206)Online publication date: 17-Oct-2018
https://dl.acm.org/doi/10.1145/3269206.3271808
Adhikari BSondhi PZhang WSharma MPrakash BChampin PGandon FMédini LLalmas MIpeirotis P(2018)Mining E-Commerce Query Relations using Customer Interaction NetworksProceedings of the 2018 World Wide Web Conference10.1145/3178876.3186174(1805-1814)Online publication date: 10-Apr-2018
https://dl.acm.org/doi/10.1145/3178876.3186174
Wang JHuang JWu DGuo JLan Y(2016)An incremental model on search engine query recommendationNeurocomputing10.1016/j.neucom.2016.09.003218:C(423-431)Online publication date: 19-Dec-2016
https://dl.acm.org/doi/10.1016/j.neucom.2016.09.003
Jiang JKe YChien PCheng PGeva STrotman ABruza PClarke CJärvelin K(2014)Learning user reformulation behavior for query auto-completionProceedings of the 37th international ACM SIGIR conference on Research & development in information retrieval10.1145/2600428.2609614(445-454)Online publication date: 3-Jul-2014
https://dl.acm.org/doi/10.1145/2600428.2609614
Chelaru SAltingovde ISiersdorfer SNejdl W(2013)Analyzing, Detecting, and Exploiting Sentiment in Web QueriesACM Transactions on the Web10.1145/25355258:1(1-28)Online publication date: 1-Dec-2013
https://dl.acm.org/doi/10.1145/2535525
Ayadi HTorjmen MDaoud MBen Jemaa MXiangji Huang JHe QIyengar ANejdl WPei JRastogi R(2013)Correlating medical-dependent query features with image retrieval models using association rulesProceedings of the 22nd ACM international conference on Information & Knowledge Management10.1145/2505515.2505580(299-308)Online publication date: 27-Oct-2013
https://dl.acm.org/doi/10.1145/2505515.2505580
Yang YCao J(2012)Feature-based recommendation framework on OLAPProceedings of the Twenty-Third Australasian Database Conference - Volume 12410.5555/2483739.2483750(81-88)Online publication date: 31-Jan-2012
https://dl.acm.org/doi/10.5555/2483739.2483750
Bordino IDonato DPoblete BChen XLebanon GWang HZaki M(2012)Extracting interesting association rules from toolbar dataProceedings of the 21st ACM international conference on Information and knowledge management10.1145/2396761.2398687(2543-2546)Online publication date: 29-Oct-2012
https://dl.acm.org/doi/10.1145/2396761.2398687
Reda APark YTiwari MPosse CShah SChen XLebanon GWang HZaki M(2012)MetaphorProceedings of the 21st ACM international conference on Information and knowledge management10.1145/2396761.2396847(664-673)Online publication date: 29-Oct-2012
https://dl.acm.org/doi/10.1145/2396761.2396847
Adeyanju ISong DAlbakour MKruschwitz UDe Roeck AFasli MHersh WCallan JMaarek YSanderson M(2012)Adaptation of the concept hierarchy model with search logs for query recommendation on intranetsProceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval10.1145/2348283.2348288(5-14)Online publication date: 12-Aug-2012
https://dl.acm.org/doi/10.1145/2348283.2348288
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Discovering search engine related queries using association rules

Evaluating leading web search engines on children's queries

Overlap Among Major Web Search Engines

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