Data mining, Hypergraph Transversals, and Machine Learning

Summary: Maps discovery of maximally-specific “interesting” sentences in databases to the hypergraph-transversal problem, enabling formal complexity analysis. Analyzes two algorithms—one efficient for small patterns (improves a special-case transversal), the other uses transversal subroutines with near-optimal bounds and ties results to exact learning. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: h9d5aed5d4df57284
Venue: PODS
Year: 1997
Pagerank: 5.7055034e-05
Overall Rank: 6,700 | 54.96%
DOI: 10.1145/263661.263684

Incoming Non-self Citations Over Time

Authors

1. Dimitrios Gunopulos (IBM)
2. Roni Khardon (Harvard University)
3. Heikki Mannila (University of Helsinki)
4. Hannu Toivonen (University of Helsinki)

BibTeX Citation

@inproceedings{gunopulos_pods97,
        address = {New York, NY, USA},
        series = {{PODS} '97},
        title = {{Data mining, Hypergraph Transversals, and Machine Learning}},
        url = {https://dl.acm.org/doi/10.1145/263661.263684},
        doi = {10.1145/263661.263684},
        booktitle = {Proceedings of the {ACM} {SIGMOD} Symposium on {Principles} of {Database} {Systems}},
        publisher = {Association for Computing Machinery},
        author = {Gunopulos, Dimitrios and Khardon, Roni and Mannila, Heikki and Toivonen, Hannu},
        year = {1997}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
308	Automatic Subspace Clustering of High Dimensional Data for Data Mining Applications	1998	SIGMOD	0.00021473921
9,390	Feasible Itemset Distributions in Data Mining: Theory and Application	2003	PODS	5.1868213e-05
13,102	How to Quickly Find a Witness	2003	PODS	4.9793485e-05

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
13	Mining Association Rules between Sets of Items in Large Databases	1993	SIGMOD	0.00064420972

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