FP-Tree and Its Variants: Towards Solving the Pattern Mining Challenges View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2018

AUTHORS

Anindita Borah , Bhabesh Nath

ABSTRACT

Mining patterns from databases is like searching for precious gems which is a gruesome task but still a rewarding one. The frequent patterns are believed to be valuable assets for the researchers that provide them useful information. The frequent and rare pattern mining paradigm is broadly divided into Apriori and FP-Tree-based approaches. Experimental results and performance evaluation available in the literature have established the fact that FP-Tree-based approaches are superior to the Apriori ones on various grounds. This paper explores the various modifications of FP-Tree that were developed to tackle the major pattern mining research challenges. Through this paper, an attempt has been made to review the usefulness and applicability of the most eminent data structure in the domain of pattern mining, the FP-Tree. More... »

PAGES

535-543

References to SciGraph publications

  • 2004. An Efficient Approach for Maintaining Association Rules Based on Adjusting FP-Tree Structures in DATABASE SYSTEMS FOR ADVANCED APPLICATIONS
  • 2013. Mining Frequent Patterns from Uncertain Data with MapReduce for Big Data Analytics in DATABASE SYSTEMS FOR ADVANCED APPLICATIONS
  • 2007-04. CanTree: a canonical-order tree for incremental frequent-pattern mining in KNOWLEDGE AND INFORMATION SYSTEMS
  • 2010. Efficient Pattern Mining of Uncertain Data with Sampling in ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING
  • 2004. FP-Bonsai: The Art of Growing and Pruning Small FP-Trees in ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING
  • 2000. Mining Access Patterns Efficiently from Web Logs in KNOWLEDGE DISCOVERY AND DATA MINING. CURRENT ISSUES AND NEW APPLICATIONS
  • 2011. RP-Tree: Rare Pattern Tree Mining in DATA WAREHOUSING AND KNOWLEDGE DISCOVERY
  • 2008. CP-Tree: A Tree Structure for Single-Pass Frequent Pattern Mining in ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING
  • 2002-10. An incremental updating algorithm for mining association rules in JOURNAL OF ELECTRONICS (CHINA)
  • 2009-04. DRFP-tree: disk-resident frequent pattern tree in APPLIED INTELLIGENCE
  • 2002. Top Down FP-Growth for Association Rule Mining in ADVANCES IN KNOWLEDGE DISCOVERY AND DATA MINING
  • Book

    TITLE

    Proceedings of First International Conference on Smart System, Innovations and Computing

    ISBN

    978-981-10-5827-1
    978-981-10-5828-8

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-981-10-5828-8_51

    DOI

    http://dx.doi.org/10.1007/978-981-10-5828-8_51

    DIMENSIONS

    https://app.dimensions.ai/details/publication/pub.1100246764


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