• gSpan

  • Referenced in 115 articles [sw11908]
  • investigate new approaches for frequent graph-based pattern mining in graph datasets and propose ... called gSpan (graph-based substructure pattern mining), which discovers frequent substructures without candidate generation. gSpan...
  • CMAR

  • Referenced in 53 articles [sw28406]
  • still suffers from the huge set of mined rules and sometimes biased classification or overfitting ... Rules. The method extends an efficient frequent pattern mining method, FP-growth, constructs a class...
  • BIDE

  • Referenced in 36 articles [sw39999]
  • that a frequent pattern mining algorithm should not mine all frequent patterns but only ... most of the previously developed closed pattern mining algorithms work under the candidate maintenance ... patterns become long. We present, BIDE, an efficient algorithm for mining frequent closed sequences without...
  • CloseGraph

  • Referenced in 31 articles [sw37017]
  • closed frequent graph patterns. Recent research on pattern discovery has progressed form mining frequent itemsets ... exploration, and etc. However, mining large graph patterns in challenging due to the presence ... subgraphs, we propose to mine closed frequent graph patterns. A graph g is closed ... support as g. A closed graph pattern mining algorithm, CloseGraph, is developed by exploring several...
  • CLOSET

  • Referenced in 51 articles [sw26986]
  • applying a compressed, frequent pattern tree FP-tree structure for mining closed itemsets without candidate ... single prefix path compression technique to identify frequent closed itemsets quickly, and (3) exploring...
  • stream

  • Referenced in 3 articles [sw23392]
  • data streams include clustering, classification and frequent pattern mining. New algorithms for these types ... experimenting with algorithms for various data stream mining tasks. The main advantage of stream ... many programming languages popular among data mining researchers (e.g., C/C++, Java and Python). In this ... stream mining tasks like classification and frequent pattern mining...
  • arules

  • Referenced in 19 articles [sw07327]
  • package arules: Mining Association Rules and Frequent Itemsets. Provides the infrastructure for representing ... manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides interfaces ... implementations of the association mining algorithms Apriori and Eclat by C. Borgelt...
  • Fr-ONT

  • Referenced in 2 articles [sw28410]
  • task of frequent concept mining: mining frequent patterns of the form of (complex) concepts expressed ... logic. We devise an algorithm for mining frequent patterns expressed in standard EL++ description logic...
  • gBoost

  • Referenced in 8 articles [sw42199]
  • classification and regression. Graph mining methods enumerate frequently appearing subgraph patterns, which can be used ... graph data, a branch-and-bound pattern search algorithm is developed based ... than the simpler method based on frequent substructure mining, because the output labels are used ... problems can be solved without modifying the pattern search algorithm...
  • COBBLER

  • Referenced in 3 articles [sw26973]
  • Pattern Discovery. The problem of mining frequent closed patterns has receivedconsiderable attention recently ... much lessredundancy compared to discovering all frequent patterns. Existingalgorithms can presently be separated into ... algorithm called COBBLERwhich can efficiently mine such datasets . COBBLER isdesigned to dynamically switch between feature...
  • eWAP-mine

  • Referenced in 1 article [sw01470]
  • mine: enhanced mining algorithm to mine web access pattern from WAP-tree. As the information ... tree (WAP-tree) mining is a frequent pattern mining technique for web log access sequences ... sequential data. WAP-tree algorithm then, mines the frequent sequences from the WAP-tree ... named eWAP-mine (enhanced web access pattern mining algorithm), which is based directly...
  • FreeSpan

  • Referenced in 1 article [sw20760]
  • FreeSpan: Frequent pattern-projected sequential pattern mining. Sequential pattern mining is an important data mining ... method, called FreeSpan (i.e., Frequent pattern-projected Sequential pattern mining). The general idea ... integrate the mining of frequent sequences with that of frequent patterns and use projected sequence ... growth of subsequence fragments. FreeSpan mines the complete set of patterns but greatly reduces...
  • AFOPT

  • Referenced in 4 articles [sw18901]
  • revisit the frequent itemset mining (FIM) problem and focus on studying the pattern growth approach ... described the implementation techniques of an adaptive pattern growth algorithm, called AFOPT, which demonstrated good ... also extended the algorithm to mine closed and maximal frequent itemsets. Comprehensive experiments were conducted...
  • PlanMine

  • Referenced in 9 articles [sw01592]
  • PlanMine sequence mining algorithm to extract patterns of events that predict failures in databases ... mining algorithms were overwhelmed by the staggering number of very frequent, but entirely unpredictive patterns...
  • SPAMS

  • Referenced in 1 article [sw02840]
  • SPAMS, to deal with the sequential patterns mining problem in data streams. This algorithm uses ... structure to maintain the set of frequent sequential patterns, i.e. SPA (Sequential Pattern Automaton ... smaller than the set of frequent sequential patterns by two or more orders of magnitude ... data structure for mining frequent sequential patterns in data streams...
  • SPMF

  • Referenced in 15 articles [sw11999]
  • mining algorithms. SPMF is a cross-platform library implemented in Java, specialized for discovering patterns ... transaction and sequence databases such as frequent itemsets, association rules and sequential patterns. The source...
  • LOGML

  • Referenced in 3 articles [sw02473]
  • simplicity with which mining algorithms (for extracting increasingly complex frequent patterns) can be specified...
  • PyNose

  • Referenced in 1 article [sw39801]
  • Python-specific test smells by mining frequent code change patterns that can be considered...
  • Krimp

  • Referenced in 19 articles [sw28422]
  • major problems in pattern mining is the explosion of the number of results. Tight constraints ... number of returned patterns. This is caused by large groups of patterns essentially describing ... principle: the best set of patterns is that set that compresses the database best ... orders of magnitude, in the number of frequent item sets. These selections, called code tables...
  • RP-Tree

  • Referenced in 3 articles [sw18882]
  • rare pattern tree mining. Most association rule mining techniques concentrate on finding frequent rules. However...