• 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]
  • Rules. The method extends an efficient frequent pattern mining method, FP-growth, constructs a class...
  • BIDE

  • Referenced in 36 articles [sw39999]
  • have presented convincing arguments that a frequent pattern mining algorithm should not mine all frequent ... patterns become long. We present, BIDE, an efficient algorithm for mining frequent closed sequences without...
  • CLOSET

  • Referenced in 51 articles [sw26986]
  • three techniques: (1) applying a compressed, frequent pattern tree FP-tree structure for mining closed ... single prefix path compression technique to identify frequent closed itemsets quickly, and (3) exploring...
  • 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 ... graph patterns in challenging due to the presence of an exponential number of frequent subgraphs ... subgraphs, we propose to mine closed frequent graph patterns. A graph g is closed...
  • arules

  • Referenced in 19 articles [sw07327]
  • manipulating and analyzing transaction data and patterns (frequent itemsets and association rules). Also provides interfaces...
  • gBoost

  • Referenced in 8 articles [sw42199]
  • regression. Graph mining methods enumerate frequently appearing subgraph patterns, which can be used as features ... subsequent classification or regression. However, frequent patterns are not necessarily informative for the given learning ... graph data, a branch-and-bound pattern search algorithm is developed based ... efficiently than the simpler method based on frequent substructure mining, because the output labels...
  • Carpenter

  • Referenced in 6 articles [sw26985]
  • Carpenter: finding closed patterns in long biological datasets. The growth of bioinformatics has resulted ... great challenge for existing (closed) frequent pattern discovery algorithms, since they have an exponential dependence...
  • SPMF

  • Referenced in 15 articles [sw11999]
  • sequence databases such as frequent itemsets, association rules and sequential patterns. The source code...
  • stream

  • Referenced in 3 articles [sw23392]
  • data streams include clustering, classification and frequent pattern mining. New algorithms for these types ... stream mining tasks like classification and frequent pattern mining...
  • 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...
  • VIATRA2

  • Referenced in 33 articles [sw03511]
  • advanced constructs for querying (e.g. recursive graph patterns) and manipulating models (e.g. generic transformation ... meta-transformation rules) in unidirectional model transformations frequently used in formal model analysis to carry...
  • Fr-ONT

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

  • Referenced in 9 articles [sw01592]
  • PlanMine sequence mining algorithm to extract patterns of events that predict failures in databases ... staggering number of very frequent, but entirely unpredictive patterns that exist in the plan database...
  • FP-growth

  • Referenced in 3 articles [sw33196]
  • generators) with the FP-growth algorithm (Frequent Pattern growth [Han et al. 2000]), which represents...
  • LOGML

  • Referenced in 3 articles [sw02473]
  • mining algorithms (for extracting increasingly complex frequent patterns) can be specified and implemented efficiently using...
  • confreq

  • Referenced in 3 articles [sw11694]
  • objects grouped according to their characteristic patterns or configurations in contingency tables. The main focus ... over and under-frequented cells or patterns. Over frequented means that the observations in this ... observed more often than expected, under-frequented means that this cell or configuration is observed ... less often than expected. In CFA a pattern or configuration that contains more observed cases...
  • Imbalanced-learn

  • Referenced in 10 articles [sw21535]
  • problem of imbalanced dataset frequently encountered in machine learning and pattern recognition. The implemented state...
  • FreeSpan

  • Referenced in 1 article [sw20760]
  • FreeSpan: Frequent pattern-projected sequential pattern mining. Sequential pattern mining is an important data mining ... pattern mining method, called FreeSpan (i.e., Frequent pattern-projected Sequential pattern mining). The general idea ... frequent sequences with that of frequent patterns and use projected sequence databases to confine...
  • ACME

  • Referenced in 1 article [sw29727]
  • scalable parallel system for extracting frequent patterns from a very long sequence. Modern applications, including ... analysis, require the extraction of frequent patterns, called motifs, from one very long (i.e., several...