Discovering Personal Gazetteers: An Interactive Clustering Approach.
Submitted by Sara on Tue, 2007-10-30 13:47.
| Publication Type | Conference Paper | |
| Year of Publication | 2004 | |
| Authors | Zhou, C.; Frankowski, D.; Ludford, P.; Shekhar, S.; Terveen, L. | |
| Conference Name | ACM international workshop on Geographic information systems | |
| Conference Location | Washington D.C. | |
| Pagination | 266-273 | |
| Conference Start Date | 12/11/2004 | |
| Publisher | ACM | |
| ISBN Number | 1-58113-979-9 | |
| Abstract | 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, density-based 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. | |
| URL | Click Here | |
| DOI | 1032222.1032261 | |