Discovery of high utility rare itemsets using PCR tree

Bhavya Shahi, Suchira Basu, M. Geetha

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

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
Externally publishedYes
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
CountryIndia
CityMoga
Period23-06-1724-06-17

Fingerprint

Marketing
Profitability
Retail stores
Data mining
Sales

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Computer Science(all)

Cite this

Shahi, B., Basu, S., & Geetha, M. (2019). Discovery of high utility rare itemsets using PCR tree. In B. K. Panigrahi, S. Tiwari, P. K. Singh, M. C. Trivedi, & K. K. Mishra (Eds.), Smart Innovations in Communication and Computational Sciences, Proceedings of ICSICCS 2017 (pp. 59-69). (Advances in Intelligent Systems and Computing; Vol. 669). Springer Verlag. https://doi.org/10.1007/978-981-10-8968-8_6
Shahi, Bhavya ; Basu, Suchira ; Geetha, M. / Discovery of high utility rare itemsets using PCR tree. Smart Innovations in Communication and Computational Sciences, Proceedings of ICSICCS 2017. editor / Bijaya Ketan Panigrahi ; Shailesh Tiwari ; Pradeep Kumar Singh ; Munesh C. Trivedi ; Krishn K. Mishra. Springer Verlag, 2019. pp. 59-69 (Advances in Intelligent Systems and Computing).
@inproceedings{6f8bb399471a45fcae4bf6edbc9605fd,
title = "Discovery of high utility rare itemsets using PCR tree",
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.",
author = "Bhavya Shahi and Suchira Basu and M. Geetha",
year = "2019",
month = "1",
day = "1",
doi = "10.1007/978-981-10-8968-8_6",
language = "English",
isbn = "9789811089671",
series = "Advances in Intelligent Systems and Computing",
publisher = "Springer Verlag",
pages = "59--69",
editor = "Panigrahi, {Bijaya Ketan} and Shailesh Tiwari and Singh, {Pradeep Kumar} and Trivedi, {Munesh C.} and Mishra, {Krishn K.}",
booktitle = "Smart Innovations in Communication and Computational Sciences, Proceedings of ICSICCS 2017",
address = "Germany",

}

Shahi, B, Basu, S & Geetha, M 2019, Discovery of high utility rare itemsets using PCR tree. in BK Panigrahi, S Tiwari, PK Singh, MC Trivedi & KK Mishra (eds), Smart Innovations in Communication and Computational Sciences, Proceedings of ICSICCS 2017. Advances in Intelligent Systems and Computing, vol. 669, Springer Verlag, pp. 59-69, International Conference on Smart Innovations in Communications and Computational Sciences, ICSICCS 2017, Moga, India, 23-06-17. https://doi.org/10.1007/978-981-10-8968-8_6

Discovery of high utility rare itemsets using PCR tree. / Shahi, Bhavya; Basu, Suchira; Geetha, M.

Smart Innovations in Communication and Computational Sciences, Proceedings of ICSICCS 2017. ed. / Bijaya Ketan Panigrahi; Shailesh Tiwari; Pradeep Kumar Singh; Munesh C. Trivedi; Krishn K. Mishra. Springer Verlag, 2019. p. 59-69 (Advances in Intelligent Systems and Computing; Vol. 669).

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

TY - GEN

T1 - Discovery of high utility rare itemsets using PCR tree

AU - Shahi, Bhavya

AU - Basu, Suchira

AU - Geetha, M.

PY - 2019/1/1

Y1 - 2019/1/1

N2 - 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.

AB - 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.

UR - http://www.scopus.com/inward/record.url?scp=85049302583&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=85049302583&partnerID=8YFLogxK

U2 - 10.1007/978-981-10-8968-8_6

DO - 10.1007/978-981-10-8968-8_6

M3 - Conference contribution

SN - 9789811089671

T3 - Advances in Intelligent Systems and Computing

SP - 59

EP - 69

BT - Smart Innovations in Communication and Computational Sciences, Proceedings of ICSICCS 2017

A2 - Panigrahi, Bijaya Ketan

A2 - Tiwari, Shailesh

A2 - Singh, Pradeep Kumar

A2 - Trivedi, Munesh C.

A2 - Mishra, Krishn K.

PB - Springer Verlag

ER -

Shahi B, Basu S, Geetha M. Discovery of high utility rare itemsets using PCR tree. In Panigrahi BK, Tiwari S, Singh PK, Trivedi MC, Mishra KK, editors, Smart Innovations in Communication and Computational Sciences, Proceedings of ICSICCS 2017. Springer Verlag. 2019. p. 59-69. (Advances in Intelligent Systems and Computing). https://doi.org/10.1007/978-981-10-8968-8_6