TY - GEN
T1 - Cross-domain review helpfulness prediction based on convolutional neural networks with auxiliary domain discriminators
AU - Chen, Cen
AU - Yang, Yinfei
AU - Zhou, Jun
AU - Li, Xiaolong
AU - Bao, Forrest Sheng
N1 - Publisher Copyright:
© 2018 Association for Computational Linguistics.
PY - 2018
Y1 - 2018
N2 - With the growing amount of reviews in ecommerce websites, it is critical to assess the helpfulness of reviews and recommend them accordingly to consumers. Recent studies on review helpfulness require plenty of labeled samples for each domain/category of interests. However, such an approach based on close-world assumption is not always practical, especially for domains with limited reviews or the "out-of-vocabulary" problem. Therefore, we propose a convolutional neural network (CNN) based model which leverages both word-level and character-based representations. To transfer knowledge between domains, we further extend our model to jointly model different domains with auxiliary domain discriminators. On the Amazon product review dataset, our approach significantly outperforms the state of the art in terms of both accuracy and cross-domain robustness.
AB - With the growing amount of reviews in ecommerce websites, it is critical to assess the helpfulness of reviews and recommend them accordingly to consumers. Recent studies on review helpfulness require plenty of labeled samples for each domain/category of interests. However, such an approach based on close-world assumption is not always practical, especially for domains with limited reviews or the "out-of-vocabulary" problem. Therefore, we propose a convolutional neural network (CNN) based model which leverages both word-level and character-based representations. To transfer knowledge between domains, we further extend our model to jointly model different domains with auxiliary domain discriminators. On the Amazon product review dataset, our approach significantly outperforms the state of the art in terms of both accuracy and cross-domain robustness.
UR - https://www.scopus.com/pages/publications/85061978247
M3 - 会议稿件
AN - SCOPUS:85061978247
T3 - NAACL HLT 2018 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies - Proceedings of the Conference
SP - 602
EP - 607
BT - Short Papers
PB - Association for Computational Linguistics (ACL)
T2 - 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL HLT 2018
Y2 - 1 June 2018 through 6 June 2018
ER -