Predict the customer behavior in the shopping by distributed learning automata

Mansour Esmaeilpour, Vahideh Naderifar, Riza Sulaiman

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

Abstract

Predict the customer behavior in the shopping is important from two aspects: one is from the perspective of goods suppliers and the other from shop owners. Both groups want to know that their customers interest in which goods and buy which sequence of the goods. In the this paper we provide a way in finding sequences of the customers' shopping, which in comparison with the previous methods, it works better and we demonstrate that it could obtain sequences of the customers' shopping in shorter time than the previous methods. Finding of the sequences is very essential for suppliers of goods and shop owners and will lead to an increase in annual profit. In this article, we provide a method of finding two-member and higher sequences by distributed learning automata; its costs is lower than the other methods. We examined it on online basket data of costumer shopping and it is clear that the results are much better.

Original languageEnglish
Title of host publicationProceedings 2010 International Symposium on Information Technology - System Development and Application and Knowledge Society, ITSim'10
Pages1668-1672
Number of pages5
Volume3
DOIs
Publication statusPublished - 2010
Event2010 International Symposium on Information Technology, ITSim'10 - Kuala Lumpur
Duration: 15 Jun 201017 Jun 2010

Other

Other2010 International Symposium on Information Technology, ITSim'10
CityKuala Lumpur
Period15/6/1017/6/10

Fingerprint

Profitability
Costs

Keywords

  • Customer
  • Learning automata
  • Predict
  • Sequence pattern
  • Shopping

ASJC Scopus subject areas

  • Computer Networks and Communications
  • Information Systems

Cite this

Esmaeilpour, M., Naderifar, V., & Sulaiman, R. (2010). Predict the customer behavior in the shopping by distributed learning automata. In Proceedings 2010 International Symposium on Information Technology - System Development and Application and Knowledge Society, ITSim'10 (Vol. 3, pp. 1668-1672). [5561500] https://doi.org/10.1109/ITSIM.2010.5561500

Predict the customer behavior in the shopping by distributed learning automata. / Esmaeilpour, Mansour; Naderifar, Vahideh; Sulaiman, Riza.

Proceedings 2010 International Symposium on Information Technology - System Development and Application and Knowledge Society, ITSim'10. Vol. 3 2010. p. 1668-1672 5561500.

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

Esmaeilpour, M, Naderifar, V & Sulaiman, R 2010, Predict the customer behavior in the shopping by distributed learning automata. in Proceedings 2010 International Symposium on Information Technology - System Development and Application and Knowledge Society, ITSim'10. vol. 3, 5561500, pp. 1668-1672, 2010 International Symposium on Information Technology, ITSim'10, Kuala Lumpur, 15/6/10. https://doi.org/10.1109/ITSIM.2010.5561500
Esmaeilpour M, Naderifar V, Sulaiman R. Predict the customer behavior in the shopping by distributed learning automata. In Proceedings 2010 International Symposium on Information Technology - System Development and Application and Knowledge Society, ITSim'10. Vol. 3. 2010. p. 1668-1672. 5561500 https://doi.org/10.1109/ITSIM.2010.5561500
Esmaeilpour, Mansour ; Naderifar, Vahideh ; Sulaiman, Riza. / Predict the customer behavior in the shopping by distributed learning automata. Proceedings 2010 International Symposium on Information Technology - System Development and Application and Knowledge Society, ITSim'10. Vol. 3 2010. pp. 1668-1672
@inproceedings{7ab8b38e33f14f128ac641580b91320c,
title = "Predict the customer behavior in the shopping by distributed learning automata",
abstract = "Predict the customer behavior in the shopping is important from two aspects: one is from the perspective of goods suppliers and the other from shop owners. Both groups want to know that their customers interest in which goods and buy which sequence of the goods. In the this paper we provide a way in finding sequences of the customers' shopping, which in comparison with the previous methods, it works better and we demonstrate that it could obtain sequences of the customers' shopping in shorter time than the previous methods. Finding of the sequences is very essential for suppliers of goods and shop owners and will lead to an increase in annual profit. In this article, we provide a method of finding two-member and higher sequences by distributed learning automata; its costs is lower than the other methods. We examined it on online basket data of costumer shopping and it is clear that the results are much better.",
keywords = "Customer, Learning automata, Predict, Sequence pattern, Shopping",
author = "Mansour Esmaeilpour and Vahideh Naderifar and Riza Sulaiman",
year = "2010",
doi = "10.1109/ITSIM.2010.5561500",
language = "English",
isbn = "9781424467181",
volume = "3",
pages = "1668--1672",
booktitle = "Proceedings 2010 International Symposium on Information Technology - System Development and Application and Knowledge Society, ITSim'10",

}

TY - GEN

T1 - Predict the customer behavior in the shopping by distributed learning automata

AU - Esmaeilpour, Mansour

AU - Naderifar, Vahideh

AU - Sulaiman, Riza

PY - 2010

Y1 - 2010

N2 - Predict the customer behavior in the shopping is important from two aspects: one is from the perspective of goods suppliers and the other from shop owners. Both groups want to know that their customers interest in which goods and buy which sequence of the goods. In the this paper we provide a way in finding sequences of the customers' shopping, which in comparison with the previous methods, it works better and we demonstrate that it could obtain sequences of the customers' shopping in shorter time than the previous methods. Finding of the sequences is very essential for suppliers of goods and shop owners and will lead to an increase in annual profit. In this article, we provide a method of finding two-member and higher sequences by distributed learning automata; its costs is lower than the other methods. We examined it on online basket data of costumer shopping and it is clear that the results are much better.

AB - Predict the customer behavior in the shopping is important from two aspects: one is from the perspective of goods suppliers and the other from shop owners. Both groups want to know that their customers interest in which goods and buy which sequence of the goods. In the this paper we provide a way in finding sequences of the customers' shopping, which in comparison with the previous methods, it works better and we demonstrate that it could obtain sequences of the customers' shopping in shorter time than the previous methods. Finding of the sequences is very essential for suppliers of goods and shop owners and will lead to an increase in annual profit. In this article, we provide a method of finding two-member and higher sequences by distributed learning automata; its costs is lower than the other methods. We examined it on online basket data of costumer shopping and it is clear that the results are much better.

KW - Customer

KW - Learning automata

KW - Predict

KW - Sequence pattern

KW - Shopping

UR - http://www.scopus.com/inward/record.url?scp=78049366195&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=78049366195&partnerID=8YFLogxK

U2 - 10.1109/ITSIM.2010.5561500

DO - 10.1109/ITSIM.2010.5561500

M3 - Conference contribution

AN - SCOPUS:78049366195

SN - 9781424467181

VL - 3

SP - 1668

EP - 1672

BT - Proceedings 2010 International Symposium on Information Technology - System Development and Application and Knowledge Society, ITSim'10

ER -