In our study, we investigate the effectiveness of different models to the purchasing behaviour at YOOCHOOSE website. This paper provide a direct method in modeling the buying pattern in a clicking session by simply using the time-stamp of the clicks and show that the result is comparable to using more massive feature engineering that requires session summarizing. Our proposed method requires much lesser feature engineering and more natural modeling of the click events directly in a typical purchasing session in e-commerce.
%0 Conference Paper
%1 Wu:2015:NMB:2813448.2813521
%A Wu, Zhenzhou
%A Tan, Bao Hong
%A Duan, Rubing
%A Liu, Yong
%A Mong Goh, Rick Siow
%B Proceedings of the 2015 International ACM Recommender Systems Challenge
%C New York, NY, USA
%D 2015
%I ACM
%K deep_learning recommendation recsys15
%P 12:1--12:4
%R 10.1145/2813448.2813521
%T Neural Modeling of Buying Behaviour for E-Commerce from Clicking Patterns
%U http://doi.acm.org/10.1145/2813448.2813521
%X In our study, we investigate the effectiveness of different models to the purchasing behaviour at YOOCHOOSE website. This paper provide a direct method in modeling the buying pattern in a clicking session by simply using the time-stamp of the clicks and show that the result is comparable to using more massive feature engineering that requires session summarizing. Our proposed method requires much lesser feature engineering and more natural modeling of the click events directly in a typical purchasing session in e-commerce.
%@ 978-1-4503-3665-9
@inproceedings{Wu:2015:NMB:2813448.2813521,
abstract = {In our study, we investigate the effectiveness of different models to the purchasing behaviour at YOOCHOOSE website. This paper provide a direct method in modeling the buying pattern in a clicking session by simply using the time-stamp of the clicks and show that the result is comparable to using more massive feature engineering that requires session summarizing. Our proposed method requires much lesser feature engineering and more natural modeling of the click events directly in a typical purchasing session in e-commerce.},
acmid = {2813521},
added-at = {2016-11-14T17:38:50.000+0100},
address = {New York, NY, USA},
articleno = {12},
author = {Wu, Zhenzhou and Tan, Bao Hong and Duan, Rubing and Liu, Yong and Mong Goh, Rick Siow},
biburl = {https://www.bibsonomy.org/bibtex/2c3afb3e5daf8fecc2e167a3eb669684c/dallmann},
booktitle = {Proceedings of the 2015 International ACM Recommender Systems Challenge},
doi = {10.1145/2813448.2813521},
interhash = {6b528414b1a401fb2f8b3e05d989b4d0},
intrahash = {c3afb3e5daf8fecc2e167a3eb669684c},
isbn = {978-1-4503-3665-9},
keywords = {deep_learning recommendation recsys15},
location = {Vienna, Austria},
numpages = {4},
pages = {12:1--12:4},
publisher = {ACM},
series = {RecSys '15 Challenge},
timestamp = {2016-11-14T17:38:50.000+0100},
title = {Neural Modeling of Buying Behaviour for E-Commerce from Clicking Patterns},
url = {http://doi.acm.org/10.1145/2813448.2813521},
year = 2015
}