Performance Analysis of Tree-Based Approaches for Pattern Mining View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2019

AUTHORS

Anindita Borah , Bhabesh Nath

ABSTRACT

Extracting meaningful patterns from databases has become a significant field of research for the data mining community. Researchers have skillfully taken up this task, contributing a range of frequent and rare pattern mining techniques. Literature subdivides the pattern mining techniques into two broad categories of level-wise and tree-based approaches. Studies illustrate that tree-based approaches outshine in terms of performance over the former ones at many instances. This paper aims to provide an empirical analysis of two well-known tree-based approaches in the field of frequent and rare pattern mining. Through this paper, an attempt has been made to let the researchers analyze the factors affecting the performance of the most widely accepted category of pattern mining techniques: the tree-based approaches. More... »

PAGES

435-448

References to SciGraph publications

  • 2004. An Efficient Approach for Maintaining Association Rules Based on Adjusting FP-Tree Structures in DATABASE SYSTEMS FOR ADVANCED APPLICATIONS
  • 2011. RP-Tree: Rare Pattern Tree Mining in DATA WAREHOUSING AND KNOWLEDGE DISCOVERY
  • 2009-04. DRFP-tree: disk-resident frequent pattern tree in APPLIED INTELLIGENCE
  • Book

    TITLE

    Computational Intelligence in Data Mining

    ISBN

    978-981-10-8054-8
    978-981-10-8055-5

    Author Affiliations

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-981-10-8055-5_39

    DOI

    http://dx.doi.org/10.1007/978-981-10-8055-5_39

    DIMENSIONS

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