TKE: Mining Top-K Frequent Episodes
- 4 September 2020
- book chapter
- Published by Springer Nature
- p. 832-845
Abstract
No abstract availableKeywords
This publication has 27 references indexed in Scilit:
- Mining cost-effective patterns in event logsKnowledge-Based Systems, 2020
- TKG: Efficient Mining of Top-K Frequent Subgraphs2019
- Large-Scale Frequent Episode Mining from Complex Event Sequences with HierarchiesACM Transactions on Intelligent Systems and Technology, 2019
- An online learning model based on episode mining for workload prediction in cloudFuture Generation Computer Systems, 2018
- DEER : Distant and Essential Episode Rules for early predictionExpert Systems with Applications, 2018
- Mining Precise-Positioning Episode Rules from Event SequencesIEEE Transactions on Knowledge and Data Engineering, 2017
- Mining Recurrent Patterns in a Dynamic Attributed Graph2017
- The SPMF Open-Source Data Mining Library Version 22016
- Online Frequent Episode Mining2015
- A unified view of the apriori-based algorithms for frequent episode discoveryKnowledge and Information Systems, 2011