Database Paper Browser

Back to papers

Mining Long Sequential Patterns in a Noisy Environment

Summary: Proposes a framework for noisy long-sequence mining via a compatibility matrix mapping observations to true symbols. Defines a match metric for real support and a border-collapse, sampling-based method to discover long patterns efficiently. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID
3367
Venue
SIGMOD
Year
2002
Pagerank
4.1945683e-05
Overall Rank
12,645 | 12.04%
DOI
-

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 1 of 1 citing papers.

Rank Citing Paper Year Venue Pagerank
6,342 A Regression-Based Temporal Pattern Mining Scheme for Data Streams 2003 VLDB 5.1034654e-05
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 7 of 7 cited papers.

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

Previous Page 1 / 1 Next

Semantically Similar Papers