Topic Tracking Model for Analyzing Consumer Purchase Behavior
Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence. Pages 1427-1431.
Abstract
We propose a new topic model for tracking time-varying 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.Tomoharu Iwata, Shinji Watanabe, Takeshi Yamada, Naonori Ueda
@inproceedings{ijcai2009p239,
title = {Topic Tracking Model for Analyzing Consumer Purchase Behavior},
author = {Iwata, Tomoharu and Watanabe, Shinji and Yamada, Takeshi and Ueda, Naonori},
booktitle = {Proceedings of the Twenty-First International Joint Conference on
Artificial Intelligence, {IJCAI-09}},
publisher = {International Joint Conferences on Artificial Intelligence},
editor = {Hiroaki Kitano},
pages = {1427--1431},
year = {2009},
url = {https://ijcai.org/proceedings/2009/239},
}
TY - CPAPER TI - Topic Tracking Model for Analyzing Consumer Purchase Behavior AU - Iwata, Tomoharu AU - Watanabe, Shinji AU - Yamada, Takeshi AU - Ueda, Naonori T2 - Proceedings of the Twenty-First International Joint Conference on Artificial Intelligence, IJCAI-09 PB - International Joint Conferences on Artificial Intelligence PY - 2009 SP - 1427 EP - 1431 UR - https://ijcai.org/proceedings/2009/239 ER -Copied
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