The DOI matches its Crossref record; 23 of the 23 references it cites were found in a registry or an index.
Mining significant semantic locations from GPS data
Abstract
With the increasing deployment and use of GPS-enabled devices, massive amounts of GPS data are becoming available. We propose a general framework for the mining of semantically meaningful, significant locations, e.g., shopping malls and restaurants, from such data. We present techniques capable of extracting semantic locations from GPS data. We capture the relationships between locations and between locations and users with a graph. Significance is then assigned to locations using random walks over the graph that propagates significance among the locations. In doing so, mutual reinforcement between location significance and user authority is exploited for determining significance, as are aspects such as the number of visits to a location, the durations of the visits, and the distances users travel to reach locations. Studies using up to 100 million GPS records from a confined spatio-temporal region demonstrate that the proposal is effective and is capable of outperforming baseline methods and an extension of an existing proposal.
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Cited by
Exploiting geographical influence for collaborative point-of-interest recommendation
Ye, M., Yin, P., Lee, W.-C., & Lee, D.-L. (2011) · Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval · doi:10.1145/2009916.2009962 · Cited by 1,111
What Your Next Check-in Might Look Like: Next Check-in Behavior Prediction
Sun, H., Cao, C., Chu, X., Hu, T., Lu, J., He, L., Wang, Z., He, H., & Xiong, H. (2023) · ACM Transactions on Intelligent Systems and Technology · doi:10.1145/3625234 · Cited by 10
Metadata
- Authors
- Cao, X., Cong, G., & Jensen, C. S.
- Venue
- Proceedings of the VLDB Endowment
- Published
- 2010-09
- Volume
- 3
- Issue
- 1-2
- Pages
- 1009-1020
- ISSN
- 2150-8097 (ISSN-L)
- OpenAlex
- W2067193733
- Cited by
- 329
- References
- 23
- FWCI
- 33.43
- Type
- journal article
- Language
- en
- Open access
- closed
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