CYUT at IJCNLP-2017 Task 3: System Report for Review Opinion Diversification

Shih-Hung Wu, Su-Yu Chang, Liang-Pu Chen


Abstract
Review Opinion Diversification (RevOpiD) 2017 is a shared task which is held in International Joint Conference on Natural Language Processing (IJCNLP). The shared task aims at selecting top-k reviews, as a summary, from a set of re-views. There are three subtasks in RevOpiD: helpfulness ranking, rep-resentativeness ranking, and ex-haustive coverage ranking. This year, our team submitted runs by three models. We focus on ranking reviews based on the helpfulness of the reviews. In the first two models, we use linear regression with two different loss functions. First one is least squares, and second one is cross entropy. The third run is a random baseline. For both k=5 and k=10, our second model gets the best scores in the official evaluation metrics.
Anthology ID:
I17-4022
Volume:
Proceedings of the IJCNLP 2017, Shared Tasks
Month:
December
Year:
2017
Address:
Taipei, Taiwan
Venue:
IJCNLP
SIG:
Publisher:
Asian Federation of Natural Language Processing
Note:
Pages:
134–137
Language:
URL:
https://aclanthology.org/I17-4022
DOI:
Bibkey:
Cite (ACL):
Shih-Hung Wu, Su-Yu Chang, and Liang-Pu Chen. 2017. CYUT at IJCNLP-2017 Task 3: System Report for Review Opinion Diversification. In Proceedings of the IJCNLP 2017, Shared Tasks, pages 134–137, Taipei, Taiwan. Asian Federation of Natural Language Processing.
Cite (Informal):
CYUT at IJCNLP-2017 Task 3: System Report for Review Opinion Diversification (Wu et al., IJCNLP 2017)
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PDF:
https://preview.aclanthology.org/ingestion-script-update/I17-4022.pdf