Enriching Topic-Based Publish-Subscribe Systems with Related Content

Summary: RMFinder: enriches topic-based pub-sub with related-message delivery. A distributed clustering algorithm builds auto-adjusting topic-clusters from topic-message similarities, adapting to shifts in focus and user interests with low overhead. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 4155
Venue: SIGMOD
Year: 2008
Pagerank: -
Overall Rank: 13,763 | 5.58%
DOI: 10.1145/1376616.1376767

Incoming Non-self Citations Over Time

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Authors

1. Rubi Boim (Tel Aviv University)
2. Tova Milo (Tel Aviv University)

BibTeX Citation

@inproceedings{boim_sigmod08,
        title = {{Enriching Topic-Based Publish-Subscribe Systems with Related Content}},
        author = {Boim, Rubi and Milo, Tova},
        series = {{SIGMOD} '08},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/1376616.1376767},
        url = {https://dl.acm.org/doi/10.1145/1376616.1376767},
        year = {2008}
}

Incoming Citations (Sorted by Pagerank)

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Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 1 of 1 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
4,954	Boosting Topic-Based Publish-Subscribe Systems with Dynamic Clustering	2007	SIGMOD	6.4300576e-05

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