Mining Open Source Software (OSS) data using association rules network

Sanjay Chawla, Bavani Arunasalam, Joseph Davis

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

12 Scopus citations

Abstract

The Open Source Software(OSS) movement has attracted considerable attention in the last few years. In this paper we report our results of mining data acquired from SourceForge.net, the largest open source software hosting website. In the process we introduce Association Rules Network(ARN), a (hyper)graphical model to represent a special class of association rules. Using ARNs we discover important relationships between the attributes of successful OSS projects. We verify and validate these relationships using Factor Analysis, a classical statistical technique related to Singular Value Decomposition(SVD).

Original languageEnglish
Title of host publicationAdvances in Knowledge Discovery and Data Mining
EditorsKyu-Young Wang, Jongwoo Jeon, Kyuseok Shim, Jaideep Srivastava
PublisherSpringer Verlag
Pages461-466
Number of pages6
ISBN (Electronic)3540047603, 9783540047605
DOIs
StatePublished - 2003
Externally publishedYes
Event7th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2003 - Seoul, Korea, Republic of
Duration: Apr 30 2003May 2 2003

Publication series

NameLecture Notes in Artificial Intelligence (Subseries of Lecture Notes in Computer Science)
Volume2637
ISSN (Print)0302-9743

Conference

Conference7th Pacific-Asia Conference on Knowledge Discovery and Data Mining, PAKDD 2003
Country/TerritoryKorea, Republic of
CitySeoul
Period04/30/0305/2/03

Keywords

  • Association rule
  • Factor analysis
  • Hypergraph clustering
  • Networks
  • Opensource software

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