LASH: Large-Scale Sequence Mining with Hierarchies

Summary: LASH provides a scalable, distributed algorithm for mining frequent sequences with hierarchical items. First parallel approach for hierarchically structured sequences, using hierarchy-aware partitioning and Pivot Sequence Miner (PSM), with MapReduce support and strong scalability. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: 5006
Venue: SIGMOD
Year: 2015
Pagerank: 5.093636e-05
Overall Rank: 12,102 | 16.97%
DOI: 10.1145/2723372.2723724

Incoming Non-self Citations Over Time

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Authors

1. Kaustubh Beedkar (University of Mannheim)
2. Rainer Gemulla (University of Mannheim)

BibTeX Citation

@inproceedings{beedkar_sigmod15,
        title = {{LASH: Large-Scale Sequence Mining with Hierarchies}},
        author = {Beedkar, Kaustubh and Gemulla, Rainer},
        series = {{SIGMOD} '15},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/2723372.2723724},
        url = {https://dl.acm.org/doi/10.1145/2723372.2723724},
        year = {2015}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

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

Rank	Cited Paper	Year	Venue	Pagerank
161	Mining Frequent Patterns without Candidate Generation	2000	SIGMOD	0.00027981772
460	Mining Generalized Association Rules	1995	VLDB	0.00018071773
4,547	Mind the Gap: Large-Scale Frequent Sequence Mining	2013	SIGMOD	6.6373455e-05

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