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Causal relation of queries from temporal logs

Published: 08 May 2007 Publication History

Abstract

In this paper, we study a new problem of mining causal relation of queries in search engine query logs. Causal relation between two queries means event on one query is the causation of some event on the other. We first detect events in query logs by efficient statistical frequency threshold. Then the causal relation of queries is mined by the geometric features of the events. Finally the Granger Causality Test (GCT) is utilized to further re-rank the causal relation of queries according to their GCT coefficients. In addition, we develop a 2-dimensional visualization tool to display the detected relationship of events in a more intuitive way. The experimental results on the MSN search engine query logs demonstrate that our approach can accurately detect the events in temporal query logs and the causal relation of queries is detected effectively.

References

[1]
C. W. J. Granger, "Investigating Causal Relations by Econometric Models and Cross-spectral Methods", Econometrica, vol. 37, pp. 424--438, 1969
[2]
C. A. Sims, "Money, Income, and Causality", the American Economic Review, vol. 62, pp. 540--552, 1972.

Cited By

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  • (2021)Evaluation of Causal Inference Techniques for AIOpsProceedings of the 3rd ACM India Joint International Conference on Data Science & Management of Data (8th ACM IKDD CODS & 26th COMAD)10.1145/3430984.3431027(188-192)Online publication date: 2-Jan-2021
  • (2021)Detecting Causal Structure on Cloud Application Microservices Using Granger Causality Models2021 IEEE 14th International Conference on Cloud Computing (CLOUD)10.1109/CLOUD53861.2021.00072(558-565)Online publication date: Sep-2021
  • (2018)The contribution of cause-effect link to representing the core of scientific paper—The role of Semantic Link NetworkPLOS ONE10.1371/journal.pone.019930313:6(e0199303)Online publication date: 21-Jun-2018
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cover image ACM Conferences
WWW '07: Proceedings of the 16th international conference on World Wide Web
May 2007
1382 pages
ISBN:9781595936547
DOI:10.1145/1242572
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 08 May 2007

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Author Tags

  1. causal relation
  2. search engine query log
  3. time series

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WWW'07
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WWW'07: 16th International World Wide Web Conference
May 8 - 12, 2007
Alberta, Banff, Canada

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

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Cited By

View all
  • (2021)Evaluation of Causal Inference Techniques for AIOpsProceedings of the 3rd ACM India Joint International Conference on Data Science & Management of Data (8th ACM IKDD CODS & 26th COMAD)10.1145/3430984.3431027(188-192)Online publication date: 2-Jan-2021
  • (2021)Detecting Causal Structure on Cloud Application Microservices Using Granger Causality Models2021 IEEE 14th International Conference on Cloud Computing (CLOUD)10.1109/CLOUD53861.2021.00072(558-565)Online publication date: Sep-2021
  • (2018)The contribution of cause-effect link to representing the core of scientific paper—The role of Semantic Link NetworkPLOS ONE10.1371/journal.pone.019930313:6(e0199303)Online publication date: 21-Jun-2018
  • (2017)Big Data and CausalityAnnals of Data Science10.1007/s40745-017-0122-35:2(133-156)Online publication date: 1-Aug-2017
  • (2015)Extracting Causal Knowledge by Time Series Analysis of EventsTransactions of the Japanese Society for Artificial Intelligence10.1527/tjsai.30.1230:1(12-21)Online publication date: 2015
  • (2013)Investigating query bursts in a web search engineWeb Intelligence and Agent Systems10.5555/2590084.259008511:2(107-124)Online publication date: 1-Apr-2013
  • (2012)Web log analysisData Mining and Knowledge Discovery10.1007/s10618-011-0228-824:3(663-696)Online publication date: 1-May-2012
  • (2011)Minimally supervised event causality identificationProceedings of the Conference on Empirical Methods in Natural Language Processing10.5555/2145432.2145466(294-303)Online publication date: 27-Jul-2011
  • (2011)Web log analysis: a review of a decade of studies about information acquisition, inspection and interpretation of user interactionData Mining and Knowledge Discovery10.1007/s10618-011-0236-8Online publication date: 6-Sep-2011
  • (2010)Optimal distance bounds for fast search on compressed time-series query logsACM Transactions on the Web10.1145/1734200.17342034:2(1-28)Online publication date: 29-Apr-2010
  • Show More Cited By

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