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Cited by 195

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Finding similar users using category-based location history

Xiao, Xiangye, Zheng, Yu, Luo, Qiong, Xie, Xing·2010·Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems

Abstract

In this paper, we aim to estimate the similarity between users according to their GPS trajectories. Our approach first models a user's GPS trajectories with a semantic location history (SLH), e.g., shopping malls → restaurants → cinemas. Then, we measure the similarity between different users' SLHs by using our maximal travel match (MTM) algorithm. The advantage of our approach lies in two aspects. First, SLH carries more semantic meanings of a user's interests beyond low-level geographic positions. Second, our approach can estimate the similarity between two users without overlaps in the geographic spaces, e.g., people living in different cities. We evaluate our method based on a real-world GPS dataset collected by 109 users in a period of 1 year. As a result, SLH-MTM outperforms the related works [4].

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Metadata

Authors
Xiao, X., Zheng, Y., Luo, Q., & Xie, X.
Venue
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Publisher
ACM
Published
2010-11-02
Pages
442-445
OpenAlex
W2075190119
Cited by
195
References
1
FWCI
11.40
Type
conference paper
Language
en
Open access
closed

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CoChat. (2026). Citation check: Finding similar users using category-based location history. https://app.cochat.ai/papers/10.1145/1869790.1869857
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Xiao, X., Zheng, Y., Luo, Q., & Xie, X. (2010). Finding similar users using category-based location history. Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems. https://doi.org/10.1145/1869790.1869857

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