2010 · 29 citations · 6 references
ComputingComputer ScienceData MiningSequence AnalysisText AnalyticsFrequent Pattern MiningPattern RecognitionSequence MiningText CollectionText MiningText PreprocessingFrequent Subsequence MiningIncremental Frequent Pattern MiningIncremental Sequence MiningMaximal Sequential Pattern MiningPattern Matching AlgorithmsPattern MiningPattern SearchingSequential Pattern Discovery
In this paper, two algorithms for discovering all the Maximal Sequential Patterns (MSP) in a document collection and in a single document are presented. The proposed algorithms follow the “pattern-growth strategy” where small frequent sequences are found first with the goal of growing them to obtain MSP. Our algorithms process the documents in an incremental way avoiding re-computing all the MSP when new documents are added. Experiments showing the performance of our algorithms and comparing against GSP, DELISP, GenPrefixSpan and cSPADE algorithms over public standard databases are also presented. Povzetek: Predstavljena sta dva algoritma za iskanje najdaljsih zaporedij v besedilu.
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Data mining: concepts and techniques
Jiawei Han, Micheline Kamber · Choice Reviews Online · 2012 · 28.9K citations
Mining association rules between sets of items in large databases
Rakesh Agrawal, Tomasz Imieliński, Arun Swami · 1993 · 14.8K citations · Full text
SPADE: An Efficient Algorithm for Mining Frequent Sequences
Mohammed J. Zaki · Machine Learning · 2001 · 1.8K citations · Full text
Frequent pattern mining: current status and future directions
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