Discovery of high utility rare itemsets using PCR tree

Bhavya Shahi, Suchira Basu*, M. Geetha

*Corresponding author for this work

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

1 Citation (Scopus)

Abstract

Data mining is used to extract interesting relationships between data in a large database. High utility rare itemsets in a transaction database can be used by retail stores to adapt their marketing strategies in order to increase their profits. Even though the itemsets mined are infrequent, since they generate a high profit for the store, marketing strategies can be used to increase the sales of these items. In this paper, a new method called the PCR tree method is proposed to generate all high utility rare itemsets while keeping the algorithm time-efficient. The proposed method generates the itemsets in one scan of the database. Results show that the time taken by the proposed method is nearly half that of the existing method, i.e. the UPR tree.

Original languageEnglish
Title of host publicationSmart Innovations in Communication and Computational Sciences, Proceedings of ICSICCS 2017
EditorsBijaya Ketan Panigrahi, Shailesh Tiwari, Pradeep Kumar Singh, Munesh C. Trivedi, Krishn K. Mishra
PublisherSpringer Verlag
Pages59-69
Number of pages11
ISBN (Print)9789811089671
DOIs
Publication statusPublished - 01-01-2019
EventInternational Conference on Smart Innovations in Communications and Computational Sciences, ICSICCS 2017 - Moga, India
Duration: 23-06-201724-06-2017

Publication series

NameAdvances in Intelligent Systems and Computing
Volume669
ISSN (Print)2194-5357

Conference

ConferenceInternational Conference on Smart Innovations in Communications and Computational Sciences, ICSICCS 2017
Country/TerritoryIndia
CityMoga
Period23-06-1724-06-17

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • General Computer Science

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