Mind the Gap: Large-Scale Frequent Sequence Mining
Summary: MG-FSM enables scalable frequent sequence mining on MapReduce with gap constraints to prune outputs. W-equivalency partitioning enables independent mining with existing algorithms; part-size optimizations cut costs, outperforming prior text mining. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Iris Miliaraki
- 2. Klaus Berberich
- 3. Rainer Gemulla
- 4. Spyros Zoupanos
Incoming Citations (Sorted by Pagerank)
Showing 4 of 4 citing papers.
| Rank | Citing Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 4,804 | A System for Management and Analysis of Preference Data | 2014 | VLDB | 5.906327e-05 |
| 6,110 | Why Big Data Industrial Systems Need Rules and What We Can Do About It | 2015 | SIGMOD | 5.2021568e-05 |
| 7,602 | Oracle Workload Intelligence | 2015 | SIGMOD | 4.6964845e-05 |
| 11,911 | LASH: Large-Scale Sequence Mining with Hierarchies | 2015 | SIGMOD | 4.1905499e-05 |
Previous
Page 1 / 1
Next
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 | 0.0010863639 |
Previous
Page 1 / 1
Next
Semantically Similar Papers
| Overall Rank | Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 9,564 | Flexible and Feasible Support Measures for Mining Frequent Patterns in Large Labeled Graphs | 2017 | SIGMOD | 4.3212967e-05 |
| 2,714 | Minimal MapReduce Algorithms | 2013 | SIGMOD | 8.2426646e-05 |
| 11,911 | LASH: Large-Scale Sequence Mining with Hierarchies | 2015 | SIGMOD | 4.1905499e-05 |
| 5,773 | Mining Frequent Patterns with Differential Privacy | 2013 | VLDB | 5.3300095e-05 |
| 13,903 | Towards Data Mining Benchmarking: A Test Bed for Performance Study of Frequent Pattern Mining | 2000 | SIGMOD | - |
| 3,061 | Mining Compressed Frequent-Pattern Sets | 2005 | VLDB | 7.6389596e-05 |
| 9,561 | T-FSM: A Task-Based System for Massively Parallel Frequent Subgraph Pattern Mining from a Big Graph | 2023 | SIGMOD | 4.3212967e-05 |
| 10,978 | Language-Model Based Informed Partition of Databases to Speed Up Pattern Mining | 2024 | SIGMOD | 4.1905499e-05 |
| 4,300 | Mining Periodic Patterns with Gap Requirement from Sequences | 2005 | SIGMOD | 6.2824978e-05 |
| 182 | Mining Frequent Patterns without Candidate Generation | 2000 | SIGMOD | 0.00036955562 |