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MARBLES: Mining association rules buried in long event sequences

https://doi.org/10.1002/sam.11199
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

inferredcites →https://doi.org/10.1007/3-540-44957-4_65openalex-snapshot
Mining Minimal Non-redundant Association Rules Using Frequent Closed Itemsets
inferredcites →https://doi.org/10.1007/978-3-540-30116-5_30openalex-snapshot
Constraint-Based Mining of Episode Rules and Optimal Window Sizes
inferredcites →https://doi.org/10.1007/978-3-540-39804-2_10openalex-snapshot
Discovering Unbounded Episodes in Sequential Data
inferredcites →https://doi.org/10.1007/978-3-642-13657-3_33openalex-snapshot
Mining Association Rules in Long Sequences
inferredcites →https://doi.org/10.1007/978-3-642-13657-3_34openalex-snapshot
Mining Closed Episodes from Event Sequences Efficiently
inferredcites →https://doi.org/10.1007/s10115-004-0174-5openalex-snapshot
Reliable detection of episodes in event sequences
inferredcites →https://doi.org/10.1007/s10115-004-0175-4openalex-snapshot
TSP: Mining top-k closed sequential patterns
inferredcites →https://doi.org/10.1007/s10618-011-0232-zopenalex-snapshot
Mining closed strict episodes
inferredcites →https://doi.org/10.1023/a:1009748302351openalex-snapshot
Discovery of Frequent Episodes in Event Sequences
inferredcites →https://doi.org/10.1109/icde.1995.380415openalex-snapshot
Mining sequential patterns
inferredcites →https://doi.org/10.1109/icde.2004.1319986openalex-snapshot
BIDE: efficient mining of frequent closed sequences
inferredcites →https://doi.org/10.1109/icdm.2001.989576openalex-snapshot
Discovering representative episodal association rules from event sequences using frequent closed episode sets and event constraints
inferredcites →https://doi.org/10.1109/icdm.2007.66openalex-snapshot
Mining Frequent Itemsets in a Stream
inferredcites →https://doi.org/10.1109/icdm.2009.23openalex-snapshot
Significance of Episodes Based on Minimal Windows
inferredcites →https://doi.org/10.1109/tkde.2002.1000341openalex-snapshot
Mining sequential patterns with regular expression constraints
inferredcites →https://doi.org/10.1109/tkde.2006.172openalex-snapshot
Discovering Frequent Closed Partial Orders from Strings
inferredcites →https://doi.org/10.1137/1.9781611972733.15openalex-snapshot
CloSpan: Mining: Closed Sequential Patterns in Large Datasets
inferredcites →https://doi.org/10.1137/1.9781611972757.34openalex-snapshot
Summarizing Sequential Data with Closed Partial Orders
inferredcites →https://doi.org/10.1137/1.9781611972757.36openalex-snapshot
Markov models for identification of significant episodes
inferredcites →https://doi.org/10.1137/1.9781611972795.28openalex-snapshot
A new constraint for mining sets in sequences
inferredcites →https://doi.org/10.1137/1.9781611972825.22openalex-snapshot
MARBLES: Mining Association Rules Buried in Long Event Sequences
inferredcites →https://doi.org/10.1145/1281192.1281238openalex-snapshot
A fast algorithm for finding frequent episodes in event streams
inferredcites →https://doi.org/10.1145/191839.191863openalex-snapshot
Combinatorial pattern discovery for scientific data
inferredcites →https://doi.org/10.1145/191843.191863openalex-snapshot
Combinatorial pattern discovery for scientific data
inferredcites →https://doi.org/10.1145/2020408.2020589openalex-snapshot
Mining closed episodes with simultaneous events
inferredcites →https://doi.org/10.1145/2541268.2541272openalex-snapshot
Formal and computational properties of the confidence boost of association rules
inferredcites →https://doi.org/10.1145/956750.956779openalex-snapshot
CLOSET+

What points at this work

Incoming claims: where this work appears in other papers’ reference lists and arguments.

inferred← citeshttps://doi.org/10.1002/widm.1524openalex-snapshot
A survey of episode mining
inferred← citeshttps://doi.org/10.1007/978-3-319-07821-2_18openalex-snapshot
Applications of Frequent Pattern Mining
inferred← citeshttps://doi.org/10.1007/978-3-319-26535-3_58openalex-snapshot
On the Discovery of Time Distance Constrained Temporal Association Rules
inferred← citeshttps://doi.org/10.1007/978-3-319-46128-1_23openalex-snapshot
Efficient Discovery of Sets of Co-occurring Items in Event Sequences
inferred← citeshttps://doi.org/10.1007/978-981-99-7254-8_46openalex-snapshot
Leveraging Sequential Episode Mining for Session-Based News Recommendation
inferred← citeshttps://doi.org/10.1007/s10618-019-00628-0openalex-snapshot
Efficiently mining cohesion-based patterns and rules in event sequences
inferred← citeshttps://doi.org/10.1016/j.eswa.2017.10.035openalex-snapshot
DEER : Distant and Essential Episode Rules for early prediction
inferred← citeshttps://doi.org/10.1109/bigdata62323.2024.10825982openalex-snapshot
Session-based News Recommendation Using Cohesive Patterns
inferred← citeshttps://doi.org/10.1109/icoac48765.2019.247131openalex-snapshot
Mining Entropy Optimized Parameter based Precise positioning Episode Rules from Event Sequences
inferred← citeshttps://doi.org/10.1109/wisa.2015.37openalex-snapshot
Mining Event Associations Using Structured Data and Classifiers
inferred← citeshttps://doi.org/10.1137/1.9781611975321.11openalex-snapshot
Mining Top-k Quantile-based Cohesive Sequential Patterns
inferred← citeshttps://doi.org/10.1145/2678025.2701407openalex-snapshot
Cohort Comparison of Event Sequences with Balanced Integration of Visual Analytics and Statistics
inferred← citeshttps://doi.org/10.1145/3167132.3167337openalex-snapshot
On the use of sequence mining within spectrum based fault localisation
inferred← citeshttps://doi.org/10.1145/3298689.3346965openalex-snapshot
Interactive evaluation of recommender systems with SNIPER
inferred← citeshttps://doi.org/10.1145/3632410.3632445openalex-snapshot
Breadth-First Search Approach for Mining Serial Episodes with Simultaneous Events
inferred← citeshttps://doi.org/10.3233/jifs-201438openalex-snapshot
Mining serial positioning episode rules by natural exponent inertia weight based swallow swarm optimization algorithm with constraint based event sequences
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