poster

Mining for insights in the search engine query stream

Authors:

Ovidiu Dan,

Pavel Dmitriev,

Ryen W. WhiteAuthors Info & Claims

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

Pages 489 - 490

https://doi.org/10.1145/2187980.2188091

Published: 16 April 2012 Publication History

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Abstract

Search engines record a large amount of metadata each time a user issues a query. While efficiently mining this data can be challeng-ing, the results can be useful in multiple ways, including monitoring search engine performance, improving search relevance, prioritizing research, and optimizing day-to-day operations. In this poster, we describe an approach for mining query log data for actionable insights - specific query segments (sets of queries) that require attention, and actions that need to be taken to improve the segments. Starting with a set of important metrics, we identify query segments that are "interesting" with respect to these metrics using a distributed frequent itemset mining algorithm.

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Cited By

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Shinde PWaghmode RLokare DHalgaonkar P(2018)Efficient Query Suggestion System using Users Search History2018 International Conference on Information , Communication, Engineering and Technology (ICICET)10.1109/ICICET.2018.8533799(1-6)Online publication date: Aug-2018
https://doi.org/10.1109/ICICET.2018.8533799
(2017)Real-time detection of navigation problems on the World Wild WebInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2016.12.002101:C(1-9)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.ijhcs.2016.12.002
Dan ODavison B(2016)Measuring and Predicting Search Engine Users’ SatisfactionACM Computing Surveys10.1145/289348649:1(1-35)Online publication date: 28-Jul-2016
https://dl.acm.org/doi/10.1145/2893486
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Index Terms

Mining for insights in the search engine query stream
1. Information systems
  1. Information retrieval

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Information & Contributors

Information

Published In

WWW '12 Companion: Proceedings of the 21st International Conference on World Wide Web

April 2012

1250 pages

ISBN:9781450312301

DOI:10.1145/2187980

General Chairs:
Alain Mille
Université de Lyon, France
,
Fabien Gandon
INRIA, France
,
Jacques Misselis
HP, France
,
Program Chairs:
Michael Rabinovich
Case Western Reserve University, USA
,
Steffen Staab
University of Koblenz-Landau, Germany

In-Cooperation

SIGWEB: ACM Special Interest Group on Hypertext, Hypermedia, and Web

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 16 April 2012

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WWW 2012

Sponsor:

Univ. de Lyon

WWW 2012: 21st World Wide Web Conference 2012

April 16 - 20, 2012

Lyon, France

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Overall Acceptance Rate 1,899 of 8,196 submissions, 23%

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Shinde PWaghmode RLokare DHalgaonkar P(2018)Efficient Query Suggestion System using Users Search History2018 International Conference on Information , Communication, Engineering and Technology (ICICET)10.1109/ICICET.2018.8533799(1-6)Online publication date: Aug-2018
https://doi.org/10.1109/ICICET.2018.8533799
(2017)Real-time detection of navigation problems on the World Wild WebInternational Journal of Human-Computer Studies10.1016/j.ijhcs.2016.12.002101:C(1-9)Online publication date: 1-May-2017
https://dl.acm.org/doi/10.1016/j.ijhcs.2016.12.002
Dan ODavison B(2016)Measuring and Predicting Search Engine Users’ SatisfactionACM Computing Surveys10.1145/289348649:1(1-35)Online publication date: 28-Jul-2016
https://dl.acm.org/doi/10.1145/2893486
Hassan AWhite RWang YJones GSheridan PKelly Dde Rijke MSakai T(2013)Toward self-correcting search enginesProceedings of the 36th international ACM SIGIR conference on Research and development in information retrieval10.1145/2484028.2484043(263-272)Online publication date: 28-Jul-2013
https://dl.acm.org/doi/10.1145/2484028.2484043

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An efficient pattern growth approach for mining fault tolerant frequent itemsets

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