HORIE: Helpfulness of Online Reviews with Improved Embedding
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-12700-7_62
Reference38 articles.
1. Agnihotri, A., Bhattacharya, S.: Online review helpfulness: role of qualitative factors. Psychol. Mark. 33(11), 1006–1017 (2016)
2. Cao, Q., Duan, W., Gan, Q.: Exploring determinants of voting for the “helpfulness’’ of online user reviews: a text mining approach. Decis. Support Syst. 50(2), 511–521 (2011)
3. Chen, C., et al.: Review helpfulness prediction with embedding-gated CNN. arXiv preprint arXiv:1808.09896 (2018)
4. Chen, C., Yang, Y., Zhou, J., Li, X., Bao, F.: Cross-domain review helpfulness prediction based on convolutional neural networks with auxiliary domain discriminators. In: Proceedings of the 2018 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers), pp. 602–607 (2018)
5. Chen, C.C., Tseng, Y.D.: Quality evaluation of product reviews using an information quality framework. Decis. Support Syst. 50(4), 755–768 (2011)
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