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Large-Scale Frequent Episode Mining from Complex Event Sequences with Hierarchies
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
inferredcites →https://doi.org/10.1006/jpdc.2000.1695openalex-snapshot
Parallel Sequence Mining on Shared-Memory Machines
inferredcites →https://doi.org/10.1007/11871637_9openalex-snapshot
VOGUE: A Novel Variable Order-Gap State Machine for Modeling Sequences
inferredcites →https://doi.org/10.1007/3-540-36175-8_4openalex-snapshot
Mining Frequent Episodes for Relating Financial Events and Stock Trends
inferredcites →https://doi.org/10.1007/978-1-4615-0953-0_2openalex-snapshot
Data Mining for Intrusion Detection
inferredcites →https://doi.org/10.1007/978-3-319-91452-7_43openalex-snapshot
Free-Rider Episode Screening via Dual Partition Model
inferredcites →https://doi.org/10.1007/978-3-540-39804-2_10openalex-snapshot
Discovering Unbounded Episodes in Sequential Data
inferredcites →https://doi.org/10.1007/bfb0014140openalex-snapshot
Mining sequential patterns: Generalizations and performance improvements
inferredcites →https://doi.org/10.1007/s10115-011-0408-2openalex-snapshot
A unified view of the apriori-based algorithms for frequent episode discovery
inferredcites →https://doi.org/10.1007/s10618-011-0233-yopenalex-snapshot
Discovering injective episodes with general partial orders
inferredcites →https://doi.org/10.1007/s10618-013-0327-9openalex-snapshot
Discovering episodes with compact minimal windows
inferredcites →https://doi.org/10.1007/s10618-015-0419-9openalex-snapshot
Ranking episodes using a partition model
inferredcites →https://doi.org/10.1016/j.datak.2013.06.005openalex-snapshot
Pattern-growth based frequent serial episode discovery
inferredcites →https://doi.org/10.1016/j.eswa.2015.02.022openalex-snapshot
Discovering utility-based episode rules in complex event sequences
inferredcites →https://doi.org/10.1016/j.eswa.2017.10.035openalex-snapshot
DEER : Distant and Essential Episode Rules for early prediction
inferredcites →https://doi.org/10.1016/j.is.2007.07.003openalex-snapshot
Efficient mining of frequent episodes from complex sequences
inferredcites →https://doi.org/10.1016/j.is.2018.05.003openalex-snapshot
Discovering and learning sensational episodes of news events
inferredcites →https://doi.org/10.1016/s0167-739x(97)00019-8openalex-snapshot
Mining generalized association rules
inferredcites →https://doi.org/10.1023/a:1009748302351openalex-snapshot
Discovery of Frequent Episodes in Event Sequences
inferredcites →https://doi.org/10.1023/b:dami.0000005258.31418.83openalex-snapshot
Mining Frequent Patterns without Candidate Generation: A Frequent-Pattern Tree Approach
inferredcites →https://doi.org/10.1109/icde.2015.7113342openalex-snapshot
Online Frequent Episode Mining
inferredcites →https://doi.org/10.1109/icde.2016.7498343openalex-snapshot
Ranking support for matched patterns over complex event streams: The CEPR system
inferredcites →https://doi.org/10.1109/icde.2017.45openalex-snapshot
Mining Precise-Positioning Episode Rules from Event Sequences
inferredcites →https://doi.org/10.1109/icdm.2004.10043openalex-snapshot
Finding Constrained Frequent Episodes Using Minimal Occurrences
inferredcites →https://doi.org/10.1109/icdm.2004.10090openalex-snapshot
Detection of Significant Sets of Episodes in Event Sequences
inferredcites →https://doi.org/10.1109/tkde.2017.2773493openalex-snapshot
Mining Precise-Positioning Episode Rules from Event Sequences
inferredcites →https://doi.org/10.1109/tkde.2018.2886189openalex-snapshot
A Transformation-Based Framework for KNN Set Similarity Search
inferredcites →https://doi.org/10.1145/1065944.1065979openalex-snapshot
A sampling-based framework for parallel data mining
inferredcites →https://doi.org/10.1145/1081870.1081937openalex-snapshot
Parallel mining of closed sequential patterns
inferredcites →https://doi.org/10.1145/1281192.1281238openalex-snapshot
A fast algorithm for finding frequent episodes in event streams
inferredcites →https://doi.org/10.1145/1935826.1935869openalex-snapshot
Scalable knowledge harvesting with high precision and high recall
inferredcites →https://doi.org/10.1145/2020408.2020468openalex-snapshot
Experiences with mining temporal event sequences from electronic medical records
inferredcites →https://doi.org/10.1145/2020408.2020589openalex-snapshot
Mining closed episodes with simultaneous events
inferredcites →https://doi.org/10.1145/2036264.2036281openalex-snapshot
Mining Concept Sequences from Large-Scale Search Logs for Context-Aware Query Suggestion
inferredcites →https://doi.org/10.1145/2487575.2487654openalex-snapshot
Mining high utility episodes in complex event sequences
inferredcites →https://doi.org/10.1145/2505515.2505575openalex-snapshot
Parallel motif extraction from very long sequences
inferredcites →https://doi.org/10.1145/967900.967932openalex-snapshot
A parallel algorithm for the extraction of structured motifs
inferredcites →https://doi.org/10.14778/2095686.2095695openalex-snapshot
Mining flipping correlations from large datasets with taxonomies
inferredcites →https://doi.org/10.24963/ijcai.2018/590openalex-snapshot
Beyond Polarity: Interpretable Financial Sentiment Analysis with Hierarchical Query-driven Attention
inferredcites →https://doi.org/10.3115/v1/e14-3011openalex-snapshot
Complexity of Word Collocation Networks: A Preliminary Structural Analysis
inferredcites →https://doi.org/10.48550/arxiv.1902.02834openalex-snapshot
The Long and the Short of It: Summarising Event Sequences with Serial Episodes
inferredcites →https://doi.org/10.5555/1760894.1760900openalex-snapshot
Mining frequent episodes for relating financial events and stock trends
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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TKE: Mining Top-K Frequent Episodes
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DSQA: A Domain Specific QA System for Smart Health Based on Knowledge Graph
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An Experimental Study of Time Series Based Patient Similarity with Graphs
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Smarter Smart Contracts: Efficient Consent Management in Health Data Sharing
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Mining Partially-Ordered Episode Rules in an Event Sequence
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Discovering Alarm Correlation Rules for Network Fault Management
inferred← citeshttps://doi.org/10.1007/978-3-030-79457-6_7openalex-snapshot
Mining Episode Rules from Event Sequences Under Non-overlapping Frequency
inferred← citeshttps://doi.org/10.1007/978-3-031-20992-5_8openalex-snapshot
MaxFEM: Mining Maximal Frequent Episodes in Complex Event Sequences
inferred← citeshttps://doi.org/10.1007/978-981-16-3964-7_6openalex-snapshot
Finding Periodic Patterns in Multiple Sequences
inferred← citeshttps://doi.org/10.1007/978-981-16-3964-7_8openalex-snapshot
Discovering Periodic High Utility Itemsets in a Discrete Sequence
inferred← citeshttps://doi.org/10.1007/s10489-023-05187-yopenalex-snapshot
Discovering frequent parallel episodes in complex event sequences by counting distinct occurrences
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CrowdMed-II: a blockchain-based framework for efficient consent management in health data sharing
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A real-time image-centric transfer function design based on incremental classification
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A Survey on Association Rule Mining for Enterprise Architecture Model Discovery
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An efficient pruning method for mining inter-sequence patterns based on pseudo-IDList
inferred← citeshttps://doi.org/10.1016/j.future.2025.107938openalex-snapshot
Mining one-off high average utility episodes for process event logs
inferred← citeshttps://doi.org/10.1016/j.ins.2020.07.043openalex-snapshot
Efficient list based mining of high average utility patterns with maximum average pruning strategies
inferred← citeshttps://doi.org/10.1016/j.ins.2024.121028openalex-snapshot
Towards episode rules with non-overlapping frequency and targeted mining
inferred← citeshttps://doi.org/10.1016/j.ins.2025.122497openalex-snapshot
OUTO-Miner: Detecting outlying occurrences in maximal frequent order-preserving patterns in time series
inferred← citeshttps://doi.org/10.1016/j.ins.2025.122871openalex-snapshot
OSP-Miner: Mining one-off weak-gap strong sequential patterns
inferred← citeshttps://doi.org/10.1016/j.knosys.2025.114803openalex-snapshot
CoTP-Miner: Co-occurrence three-way sequential pattern mining
inferred← citeshttps://doi.org/10.1016/j.net.2022.07.006openalex-snapshot
ADA: Advanced data analytics methods for abnormal frequent episodes in the baseline data of ISD
inferred← citeshttps://doi.org/10.1080/03772063.2021.2021815openalex-snapshot
Natural Exponent Inertia Weight based Particle Swarm Optimization for Mining Serial Episode Rules from Event Sequences
inferred← citeshttps://doi.org/10.1093/comjnl/bxac031openalex-snapshot
Mining Frequent Serial Positioning Episode Rules with Forward and Backward Search Technique from Event Sequences
inferred← citeshttps://doi.org/10.1109/access.2022.3228962openalex-snapshot
A Scalable Analytical Framework for Complex Event Episode Mining With Various Domains Applications
inferred← citeshttps://doi.org/10.1109/bigdata59044.2023.10386577openalex-snapshot
Online Closed Episode Mining with Root-Order Decomposition
inferred← citeshttps://doi.org/10.1109/icdmw53433.2021.00076openalex-snapshot
Sequence Prediction using Partially-Ordered Episode Rules
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A Survey of Repetitive Sequential Pattern Mining
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Cross-Layer Alarm Association Rules Discovery of Cloud-Network based on Knowledge Graph
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Discovering High Utility Episodes in Sequences
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OER-Miner: One-Off Episode Rule Mining for Process Event Logs
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OPM-Miner: One-Off Sequential Pattern Mining for Multivariate Time Series Analysis
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FNP-Miner: Fuzzy Three-Way Nonoverlapping Sequential Pattern Mining
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MCoR-Miner: Maximal Co-Occurrence Nonoverlapping Sequential Rule Mining
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COPP-Miner: Top-k Contrast Order-Preserving Pattern Mining for Time Series Classification
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RNP-Miner: Repetitive Nonoverlapping Sequential Pattern Mining
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OPF-Miner: Order-Preserving Pattern Mining With Forgetting Mechanism for Time Series
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CoNR-Miner: Self-Adaptive Co-Occurrence Nonoverlapping Sequential Rule Mining
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Shapley Distance and Shapley Index for Some Special Graphs
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Financial Defaulter Detection on Online Credit Payment via Multi-view Attributed Heterogeneous Information Network
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Hunting Temporal Bumps in Graphs with Dynamic Vertex Properties
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Breadth-First Search Approach for Mining Serial Episodes with Simultaneous Events
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Co-occurrence Order-preserving Pattern Mining with Keypoint Alignment for Time Series
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Mining Repetitive Negative Sequential Patterns with Gap Constraints
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Scalable Maximal Frequent Episode Mining with Desbordante
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On Real-time Failure Localization via Instance Correlation in Optical Transport Networks
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Learn Smart with Less: Building Better Online Decision Trees with Fewer Training Examples
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Mining serial positioning episode rules by natural exponent inertia weight based swallow swarm optimization algorithm with constraint based event sequences
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From basic approaches to novel challenges and applications in Sequential Pattern Mining
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THUE: Discovering Top-K High Utility Episodes
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