Database Paper Browser

Back to papers

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
4944
Venue
SIGMOD
Year
2015
Pagerank
4.1945683e-05
Overall Rank
11,903 | 17.20%
DOI
10.1145/2723372.2723724

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

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
181 Mining Frequent Patterns without Candidate Generation 2000 SIGMOD 0.00036992674
403 Mining Generalized Association Rules 1995 VLDB 0.00024148455
3,989 Mind the Gap: Large-Scale Frequent Sequence Mining 2013 SIGMOD 6.5583327e-05
Previous Page 1 / 1 Next

Semantically Similar Papers