• gSpan

  • Referenced in 115 articles [sw11908]
  • gSpan: graph-based substructure pattern mining. We investigate new approaches for frequent graph-based pattern ... algorithm called gSpan (graph-based substructure pattern mining), which discovers frequent substructures without candidate generation...
  • PrefixSpan

  • Referenced in 85 articles [sw20761]
  • prefix-projected pattern growth. Sequential pattern mining is an important data mining problem with broad ... Most of the previously developed sequential pattern mining methods follow the methodology of Apriori which ... paper, we propose a novel sequential pattern mining method, called PrefixSpan (i.e., Prefix-projected Sequential ... pattern mining), which explores prefix-projection in sequential pattern mining. PrefixSpan mines the complete...
  • BIDE

  • Referenced in 36 articles [sw39999]
  • presented convincing arguments that a frequent pattern mining algorithm should not mine all frequent patterns ... 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...
  • CMAR

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

  • Referenced in 39 articles [sw37018]
  • CloSpan: Closed Sequential Pattern Mining Package. CloSpan is a software package of mining closed sequential ... patterns in a sequence database. Given a collection of sequences and a minimum support threshold ... following paper, CloSpan: Mining Closed Sequential Patterns in Large Datasets ... Proc. of 2003 SIAM Int. Conf. Data Mining...
  • CloseGraph

  • Referenced in 31 articles [sw37017]
  • CloseGraph: mining closed frequent graph patterns. Recent research on pattern discovery has progressed form ... mining frequent itemsets and sequences to mining structured patterns including trees, lattices, and graphs ... exploration, and etc. However, mining large graph patterns in challenging due to the presence ... support as g. A closed graph pattern mining algorithm, CloseGraph, is developed by exploring several...
  • Krimp

  • Referenced in 19 articles [sw28422]
  • major problems in pattern mining is the explosion of the number of results. Tight constraints ... explosion in the number of returned patterns. This is caused by large groups of patterns...
  • ROCK

  • Referenced in 73 articles [sw37720]
  • attributes. Clustering, in data mining, is useful to discover distribution patterns in the underlying data...
  • CLOSET

  • Referenced in 51 articles [sw26986]
  • applying a compressed, frequent pattern tree FP-tree structure for mining closed itemsets without candidate...
  • SPMF

  • Referenced in 15 articles [sw11999]
  • SPMF: a Java open-source pattern mining library. We present SPMF, an open-source data ... mining algorithms. SPMF is a cross-platform library implemented in Java, specialized for discovering patterns...
  • Carpenter

  • Referenced in 6 articles [sw26985]
  • magnitude better than previous closed pattern mining algorithms like CLOSET and CHARM...
  • VIKAMINE

  • Referenced in 4 articles [sw21460]
  • VIKAMINE -- open-source subgroup discovery, pattern mining, and analytics. This paper presents an overview ... VIKAMINE system for subgroup discovery, pattern mining and analytics. As of VIKAMINE version...
  • CompLearn

  • Referenced in 5 articles [sw10681]
  • used is powerful because it can mine patterns in completely different domains. It can classify...
  • See5

  • Referenced in 9 articles [sw12178]
  • See5 and C5.0: Data mining is all about extracting patterns from an organization’s stored ... situations as an aid to decision-making. Patterns often concern the categories to which situations ... counterpart C5.0 are sophisticated data mining tools for discovering patterns that delineate categories, assembling them...
  • stream

  • Referenced in 3 articles [sw23392]
  • streams include clustering, classification and frequent pattern mining. New algorithms for these types of data ... mining tasks like classification and frequent pattern mining...
  • SPADE

  • Referenced in 89 articles [sw02226]
  • algorithm for fast discovery of Sequential Patterns. The existing solutions to this problem make repeated ... discuss how the results of sequence mining can be applied in a real application domain...
  • PlanMine

  • Referenced in 9 articles [sw01592]
  • paper presents the PlanMine sequence mining algorithm to extract patterns of events that predict failures ... mining algorithms were overwhelmed by the staggering number of very frequent, but entirely unpredictive patterns...
  • 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 ... order of magnitudebetter than previous closed pattern mining algorithmslike CHARM, CLOSET+ and CARPENTER...
  • DynaMine

  • Referenced in 4 articles [sw33951]
  • DynaMine: finding common error patterns by mining software revision histories. A great deal of attention ... application-specific coding patterns. Potential patterns discovered through mining are passed to a dynamic analysis ... user.The combination of revision history mining and dynamic analysis techniques leveraged in DynaMine proves effective ... mining revision histories, we have discovered 56 previously unknown, highly application-specific patterns...
  • iZi

  • Referenced in 2 articles [sw10113]
  • toolkit for pattern mining problems. Pattern mining problems are useful in many applications...