Topic tracking model for analyzing consumer purchase behavior

Tomoharu Iwata, Shinji Watanabe, Takeshi Yamada, Naonori Ueda

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

92 Citations (Scopus)

Abstract

We propose a new topic model for tracking timevarying consumer purchase behavior, in which consumer interests and item trends change over time. The proposed model can adaptively track changes in interests and trends based on current purchase logs and previously estimated interests and trends. The online nature of the proposed method means we do not need to store past data for current inferences and so we can considerably reduce the computational cost and the memory requirement. We use real purchase logs to demonstrate the effectiveness of the proposed method in terms of the prediction accuracy of purchase behavior and the computational cost of the inference.

Original languageEnglish
Title of host publicationIJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence
Pages1427-1432
Number of pages6
Publication statusPublished - 2009
Externally publishedYes
Event21st International Joint Conference on Artificial Intelligence, IJCAI-09 - Pasadena, CA, United States
Duration: 2009 Jul 112009 Jul 17

Other

Other21st International Joint Conference on Artificial Intelligence, IJCAI-09
CountryUnited States
CityPasadena, CA
Period09/7/1109/7/17

Fingerprint

Consumer behavior
Costs
Data storage equipment

ASJC Scopus subject areas

  • Artificial Intelligence

Cite this

Iwata, T., Watanabe, S., Yamada, T., & Ueda, N. (2009). Topic tracking model for analyzing consumer purchase behavior. In IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence (pp. 1427-1432)

Topic tracking model for analyzing consumer purchase behavior. / Iwata, Tomoharu; Watanabe, Shinji; Yamada, Takeshi; Ueda, Naonori.

IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence. 2009. p. 1427-1432.

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

Iwata, T, Watanabe, S, Yamada, T & Ueda, N 2009, Topic tracking model for analyzing consumer purchase behavior. in IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence. pp. 1427-1432, 21st International Joint Conference on Artificial Intelligence, IJCAI-09, Pasadena, CA, United States, 09/7/11.
Iwata T, Watanabe S, Yamada T, Ueda N. Topic tracking model for analyzing consumer purchase behavior. In IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence. 2009. p. 1427-1432
Iwata, Tomoharu ; Watanabe, Shinji ; Yamada, Takeshi ; Ueda, Naonori. / Topic tracking model for analyzing consumer purchase behavior. IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence. 2009. pp. 1427-1432
@inproceedings{2799d30b496f41a49cedb5aeea3ea52e,
title = "Topic tracking model for analyzing consumer purchase behavior",
abstract = "We propose a new topic model for tracking timevarying consumer purchase behavior, in which consumer interests and item trends change over time. The proposed model can adaptively track changes in interests and trends based on current purchase logs and previously estimated interests and trends. The online nature of the proposed method means we do not need to store past data for current inferences and so we can considerably reduce the computational cost and the memory requirement. We use real purchase logs to demonstrate the effectiveness of the proposed method in terms of the prediction accuracy of purchase behavior and the computational cost of the inference.",
author = "Tomoharu Iwata and Shinji Watanabe and Takeshi Yamada and Naonori Ueda",
year = "2009",
language = "English",
isbn = "9781577354260",
pages = "1427--1432",
booktitle = "IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence",

}

TY - GEN

T1 - Topic tracking model for analyzing consumer purchase behavior

AU - Iwata, Tomoharu

AU - Watanabe, Shinji

AU - Yamada, Takeshi

AU - Ueda, Naonori

PY - 2009

Y1 - 2009

N2 - We propose a new topic model for tracking timevarying consumer purchase behavior, in which consumer interests and item trends change over time. The proposed model can adaptively track changes in interests and trends based on current purchase logs and previously estimated interests and trends. The online nature of the proposed method means we do not need to store past data for current inferences and so we can considerably reduce the computational cost and the memory requirement. We use real purchase logs to demonstrate the effectiveness of the proposed method in terms of the prediction accuracy of purchase behavior and the computational cost of the inference.

AB - We propose a new topic model for tracking timevarying consumer purchase behavior, in which consumer interests and item trends change over time. The proposed model can adaptively track changes in interests and trends based on current purchase logs and previously estimated interests and trends. The online nature of the proposed method means we do not need to store past data for current inferences and so we can considerably reduce the computational cost and the memory requirement. We use real purchase logs to demonstrate the effectiveness of the proposed method in terms of the prediction accuracy of purchase behavior and the computational cost of the inference.

UR - http://www.scopus.com/inward/record.url?scp=77956207114&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=77956207114&partnerID=8YFLogxK

M3 - Conference contribution

SN - 9781577354260

SP - 1427

EP - 1432

BT - IJCAI-09 - Proceedings of the 21st International Joint Conference on Artificial Intelligence

ER -