Re-mining positive and negative association mining results

Ayhan Demiriz, Gurdal Ertek, Tankut Atan, Ufuk Kula

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Citations (Scopus)


Positive and negative association mining are well-known and extensively studied data mining techniques to analyze market basket data. Efficient algorithms exist to find both types of association, separately or simultaneously. Association mining is performed by operating on the transaction data. Despite being an integral part of the transaction data, the pricing and time information has not been incorporated into market basket analysis so far, and additional attributes have been handled using quantitative association mining. In this paper, a new approach is proposed to incorporate price, time and domain related attributes into data mining by re-mining the association mining results. The underlying factors behind positive and negative relationships, as indicated by the association rules, are characterized and described through the second data mining stage re-mining. The applicability of the methodology is demonstrated by analyzing data coming from apparel retailing industry, where price markdown is an essential tool for promoting sales and generating increased revenue.

Original languageEnglish
Title of host publicationAdvances in Data Mining
Subtitle of host publicationApplications and Theoretical Aspects - 10th Industrial Conference, ICDM 2010, Proceedings
Number of pages14
Publication statusPublished - 2010
Externally publishedYes
Event10th Industrial Conference on Advances in Data Mining, ICDM 2010 - Berlin, Germany
Duration: Jul 12 2010Jul 14 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume6171 LNAI
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349


Conference10th Industrial Conference on Advances in Data Mining, ICDM 2010

ASJC Scopus subject areas

  • Theoretical Computer Science
  • General Computer Science


Dive into the research topics of 'Re-mining positive and negative association mining results'. Together they form a unique fingerprint.

Cite this