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2004
ACM

Discovering personal gazetteers: an interactive clustering approach

11 years 2 months ago
Discovering personal gazetteers: an interactive clustering approach
Personal gazetteers record individuals' most important places, such as home, work, grocery store, etc. Using personal gazetteers in location-aware applications offers additional functionality and improves the user experience. However, systems then need some way to acquire them. This paper explores the use of novel semi-automatic techniques to discover gazetteers from users' travel patterns (time-stamped location data). There has been previous work on this problem, e.g., using ad hoc algorithms [13] or K-Means clustering [4]; however, both approaches have shortcomings. This paper explores a deterministic, densitybased clustering algorithm that also uses temporal techniques to reduce the number of uninteresting places that are discovered. We introduce a general framework for evaluating personal gazetteer discovery algorithms and use it to demonstrate the advantages of our algorithm over previous approaches. Categories and Subject Descriptors H.3.3 [Information Search and Retri...
Changqing Zhou, Dan Frankowski, Pamela J. Ludford,
Added 11 Nov 2009
Updated 11 Nov 2009
Type Conference
Year 2004
Where GIS
Authors Changqing Zhou, Dan Frankowski, Pamela J. Ludford, Shashi Shekhar, Loren G. Terveen
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