EBM - An Entropy-Based Model to Infer Social Strength from Spatiotemporal Data

Summary: Entropy-based model (EBM) to infer social ties and their strength from spatiotemporal co-occurrences. Jointly models diversity and weighted frequency, adapts to location sparsity, and outperforms baselines on real-world location and social-network data. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4770
Venue: SIGMOD
Year: 2013
Pagerank: 6.5359356e-05
Overall Rank: 4,729 | 67.56%
DOI: 10.1145/2463676.2465301

Incoming Non-self Citations Over Time

Authors

1. Huy Pham (University of Southern California)
2. Cyrus Shahabi (University of Southern California)
3. Yan Liu (University of Southern California)

BibTeX Citation

@inproceedings{pham_sigmod13,
        title = {{EBM - An Entropy-Based Model to Infer Social Strength from Spatiotemporal Data}},
        author = {Pham, Huy and Shahabi, Cyrus and Liu, Yan},
        series = {{SIGMOD} '13},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2463676.2465301},
        url = {https://dl.acm.org/doi/10.1145/2463676.2465301},
        year = {2013}
}

Incoming Citations (Sorted by Pagerank)

Showing 2 of 2 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
2,696	Trajectory Simplification: On Minimizing the Direction-based Error	2015	VLDB	8.24578e-05
4,651	Density-based Place Clustering in Geo-Social Networks	2014	SIGMOD	6.585234e-05

Outgoing Citations (Sorted by Pagerank)

Showing 0 of 0 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank

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