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Discovering geographical-specific interests from web click data

Published: 22 April 2008 Publication History

Abstract

As the Internet continues to play an important role in many business applications, it becomes vital to increase the competitive edge by offering geographically tailored contents that reflect the common interests of the geographical region of the web visitors. In this paper, we define the problem of mining geographical-specific interests patterns. We utilize the quadtree to model the influence distributions of different features, and design an algorithm called Flex-iPROBER to mine geographical-specific interests patterns that are significant in a local region. We further examine how these patterns can change over time and develop an algorithm called MineGIC to efficiently discover pattern changes. Experiment results demonstrate that the proposed algorithms are scalable and efficient. Patterns discovered from real world web click datasets reveal interesting patterns and show the evolution of the interests of people in those regions.

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Cited By

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  • (2010)TWinnerProceedings of the 6th Workshop on Geographic Information Retrieval10.1145/1722080.1722093(1-8)Online publication date: 18-Feb-2010
  • (2010)TweethoodProceedings of the 2010 IEEE Second International Conference on Social Computing10.1109/SocialCom.2010.30(153-160)Online publication date: 20-Aug-2010
  • (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
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  1. Discovering geographical-specific interests from web click data

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    cover image ACM Other conferences
    LOCWEB '08: Proceedings of the first international workshop on Location and the web
    April 2008
    192 pages
    ISBN:9781605581606
    DOI:10.1145/1367798
    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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    Publication History

    Published: 22 April 2008

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    Author Tags

    1. geographic-specific interest pattern
    2. influence model
    3. spatio-temporal data

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    Cited By

    View all
    • (2010)TWinnerProceedings of the 6th Workshop on Geographic Information Retrieval10.1145/1722080.1722093(1-8)Online publication date: 18-Feb-2010
    • (2010)TweethoodProceedings of the 2010 IEEE Second International Conference on Social Computing10.1109/SocialCom.2010.30(153-160)Online publication date: 20-Aug-2010
    • (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
    • (2008)Towards Click-Based Models of Geographic Interests in Web SearchProceedings of the 2008 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 0110.1109/WIIAT.2008.365(293-299)Online publication date: 9-Dec-2008

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