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Term weighting approaches for mining significant locations from personal location logs

Qiu, Zhengwei and Gurrin, Cathal and Doherty, Aiden R. and Smeaton, Alan F. (2010) Term weighting approaches for mining significant locations from personal location logs. In: CIT 2010 - 10th IEEE International Conference on Computer and Information Technology , 29 June -1 July 2010, Bradford, UK. (In Press)

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In this paper, we describe experiments into the application of term weighting techniques from text retrieval to support the automatic identification of significant locations from a large location log, which we consider to be important for supporting many location-based social network applications. We identify the fact that the distribution of locations follows a similar shaped distribution to that of terms in a language and in so doing motivate our use of term weighting techniques. Using this information we then show that these proven techniques can be used to automatically identify social visits and “pass through” locations, as well as standard home and work locations. We also suggest that it is possible to classify whether an extended segment of personal location data may be a tourist trip, business trip or a typical working (at home) period of time.

Item Type:Conference or Workshop Item (Paper)
Event Type:Conference
Uncontrolled Keywords:location; power-law distribution; GPS; important locations; text retrieval;
Subjects:Computer Science > Lifelog
Computer Science > Information retrieval
DCU Faculties and Centres:Research Initiatives and Centres > Centre for Digital Video Processing (CDVP)
DCU Faculties and Schools > Faculty of Engineering and Computing > School of Computing
Research Initiatives and Centres > CLARITY: The Centre for Sensor Web Technologies
Official URL:
Copyright Information:©2010 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE.
Funders:Science Foundation Ireland
ID Code:15399
Deposited On:09 Jun 2010 14:52 by Zhengwei Qiu. Last Modified 17 Feb 2017 10:36

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