research-article

Modeling and visualizing geo-sensitive queries based on user clicks

Authors:

Ziming Zhuang,

Cliff Brunk,

C. Lee GilesAuthors Info & Claims

LOCWEB '08: Proceedings of the first international workshop on Location and the web

Pages 73 - 76

https://doi.org/10.1145/1367798.1367811

Published: 22 April 2008 Publication History

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Abstract

The number of search queries that are associated with geographical locations, either explicitly or implicitly, has been quadrupled in recent years. For such geo-sensitive queries, the ability to accurately infer users' geographical preference greatly enhances their search experience. By mining past user clicks and constructing a geographical click probability distribution model, we address two important issues in spatial Web search: how do we determine whether a search query is geo-sensitive, and how do we detect, disambiguate, and visualize the associated geographical location(s). We present our empirical study on a large-scale dataset with about 9,000 unique queries randomly drawn from the logs of a popular commercial search engine Yahoo! Search, and about 430 million user clicks on 1.6M unique Web pages over an eight-month period. Our classification method achieved recall of 0.98 and precision of 0.75 in identifying geo-sensitive search queries. We also present our preliminary findings in using geographical click probability distributions to cluster search results for queries with geographical ambiguities.

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Cited By

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Guo JLan Y(2020)Query ClassificationQuery Understanding for Search Engines10.1007/978-3-030-58334-7_2(15-41)Online publication date: 2-Dec-2020
https://doi.org/10.1007/978-3-030-58334-7_2
Ren YTomko MSalim FChan JClarke CSanderson M(2018)A Location-Query-Browse Graph for Contextual RecommendationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.276605930:2(204-218)Online publication date: 1-Feb-2018
https://doi.org/10.1109/TKDE.2017.2766059
Hu YKang CTang JYin DChang Y(2017)Large-Scale Location Prediction for Web PagesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.270263129:9(1902-1915)Online publication date: 1-Sep-2017
https://doi.org/10.1109/TKDE.2017.2702631
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Index Terms

Modeling and visualizing geo-sensitive queries based on user clicks
1. Information systems
  1. Information retrieval
    1. Information retrieval query processing

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Published In

LOCWEB '08: Proceedings of the first international workshop on Location and the web

April 2008

192 pages

ISBN:9781605581606

DOI:10.1145/1367798

Conference Chairs:
Susanne Boll
University of Oldenburg
,
Christopher Jones
Cardiff University
,
Eric Kansa
UC Berkeley
,
Puneet Kishor
University of Wisconsin-Madison
,
Mor Naaman
Yahoo!, Inc.
,
Ross Purves
University of Zurich
,
Arno Scharl
MODUL University Vienna
,
Erik Wilde
UC Berkeley

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

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 22 April 2008

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WWW '08

WWW '08: The 17th International World Wide Web Conference

April 22, 2008

Beijing, China

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Overall Acceptance Rate 4 of 5 submissions, 80%

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Guo JLan Y(2020)Query ClassificationQuery Understanding for Search Engines10.1007/978-3-030-58334-7_2(15-41)Online publication date: 2-Dec-2020
https://doi.org/10.1007/978-3-030-58334-7_2
Ren YTomko MSalim FChan JClarke CSanderson M(2018)A Location-Query-Browse Graph for Contextual RecommendationIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.276605930:2(204-218)Online publication date: 1-Feb-2018
https://doi.org/10.1109/TKDE.2017.2766059
Hu YKang CTang JYin DChang Y(2017)Large-Scale Location Prediction for Web PagesIEEE Transactions on Knowledge and Data Engineering10.1109/TKDE.2017.270263129:9(1902-1915)Online publication date: 1-Sep-2017
https://doi.org/10.1109/TKDE.2017.2702631
Thuraisingham BAbrol SHeatherly RKantarcioglu MKhadilkar VKhan L(2016)Developments and Challenges in Location MiningAnalyzing and Securing Social Networks10.1201/b19566-13(99-112)Online publication date: 31-Mar-2016
https://doi.org/10.1201/b19566-13
O’Hare NMurdock V(2012)Modeling locations with social mediaInformation Retrieval10.1007/s10791-012-9195-y16:1(30-62)Online publication date: 11-Apr-2012
https://doi.org/10.1007/s10791-012-9195-y
Bennett PRadlinski FWhite RYilmaz EMa WNie JBaeza-Yates RChua TCroft W(2011)Inferring and using location metadata to personalize web searchProceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval10.1145/2009916.2009938(135-144)Online publication date: 24-Jul-2011
https://dl.acm.org/doi/10.1145/2009916.2009938
Abrol SKhan LPurves RClough PJones C(2010)TWinnerProceedings of the 6th Workshop on Geographic Information Retrieval10.1145/1722080.1722093(1-8)Online publication date: 18-Feb-2010
https://dl.acm.org/doi/10.1145/1722080.1722093
Hassan AJones RDiaz FWolfson OAgrawal DLu C(2009)A case study of using geographic cues to predict query news intentProceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems10.1145/1653771.1653780(33-41)Online publication date: 4-Nov-2009
https://dl.acm.org/doi/10.1145/1653771.1653780
Serdyukov PMurdock Vvan Zwol RAllan JAslam JSanderson MZhai CZobel J(2009)Placing flickr photos on a mapProceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval10.1145/1571941.1572025(484-491)Online publication date: 19-Jul-2009
https://dl.acm.org/doi/10.1145/1571941.1572025
Yi XRaghavan HLeggetter CQuemada JLeón GMaarek YNejdl W(2009)Discovering users' specific geo intention in web searchProceedings of the 18th international conference on World wide web10.1145/1526709.1526774(481-490)Online publication date: 20-Apr-2009
https://dl.acm.org/doi/10.1145/1526709.1526774
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Towards Click-Based Models of Geographic Interests in Web Search

A case study of using geographic cues to predict query news intent

A click model for time-sensitive queries

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