research-article

Temporal query log profiling to improve web search ranking

Authors:

Alexander Kotov,

Yi ChangAuthors Info & Claims

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

Pages 1149 - 1158

https://doi.org/10.1145/1871437.1871583

Published: 26 October 2010 Publication History

Abstract

Temporal information can be leveraged and incorporated to improve web search ranking. In this work, we propose a method to improve the ranking of search results by identifying the fundamental properties of temporal behavior of low-quality hosts and spam-prone queries in search logs and modeling those properties as quantifiable features. In particular, we introduce the concepts of host churn, a measure of changes in host visibility for user queries, and query volatility, a measure of semantic instability of query results, and propose the methods for construction of temporal profiles from search query logs that can be used for estimation of a set of features based on the introduced concepts. The utility of the proposed concepts has been experimentally demonstrated for two language-independent search tasks: the regression-based ranking of search results and a novel classification problem of detecting spam-prone queries introduced in this work.

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Cited By

Huang CWang D(2017)Exploring Scalability and Time-Sensitiveness in Reliable Social Sensing With Accuracy AssessmentIEEE Access10.1109/ACCESS.2017.27074805(14405-14418)Online publication date: 2017
https://doi.org/10.1109/ACCESS.2017.2707480
Gulati PSharma A(2013)Intercepting temporal constraints for searching images over the web2013 International Conference on Information Systems and Computer Networks10.1109/ICISCON.2013.6524188(129-132)Online publication date: Mar-2013
https://doi.org/10.1109/ICISCON.2013.6524188

Index Terms

Temporal query log profiling to improve web search ranking
1. Applied computing
  1. Document management and text processing
    1. Document capture
      1. Document analysis
2. Information systems
  1. Information retrieval

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cover image ACM Conferences

CIKM '10: Proceedings of the 19th ACM international conference on Information and knowledge management

October 2010

2036 pages

ISBN:9781450300995

DOI:10.1145/1871437

General Chair:
Jimmy Huang
York University, Canada
,
Program Chairs:
Nick Koudas
University of Toronto, Canada
,
Gareth Jones
Dublin City University, Ireland
,
Xindong Wu
University of Vermont, USA
,
Kevyn Collins-Thompson
Microsoft Research, USA
,
Aijun An
York University, Canada

Copyright © 2010 ACM.

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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Published: 26 October 2010

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October 26 - 30, 2010

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Cited By

Huang CWang D(2017)Exploring Scalability and Time-Sensitiveness in Reliable Social Sensing With Accuracy AssessmentIEEE Access10.1109/ACCESS.2017.27074805(14405-14418)Online publication date: 2017
https://doi.org/10.1109/ACCESS.2017.2707480
Gulati PSharma A(2013)Intercepting temporal constraints for searching images over the web2013 International Conference on Information Systems and Computer Networks10.1109/ICISCON.2013.6524188(129-132)Online publication date: Mar-2013
https://doi.org/10.1109/ICISCON.2013.6524188

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