bunji at SemEval-2017 Task 3: Combination of Neural Similarity Features and Comment Plausibility Features

Yuta Koreeda, Takuya Hashito, Yoshiki Niwa, Misa Sato, Toshihiko Yanase, Kenzo Kurotsuchi, Kohsuke Yanai


Abstract
This paper describes a text-ranking system developed by bunji team in SemEval-2017 Task 3: Community Question Answering, Subtask A and C. The goal of the task is to re-rank the comments in a question-and-answer forum such that useful comments for answering the question are ranked high. We proposed a method that combines neural similarity features and hand-crafted comment plausibility features, and we modeled inter-comments relationship using conditional random field. Our approach obtained the fifth place in the Subtask A and the second place in the Subtask C.
Anthology ID:
S17-2058
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Venue:
*SEMEVAL
SIGs:
SIGLEX | SIGSEM
Publisher:
Association for Computational Linguistics
Note:
Pages:
353–359
Language:
URL:
https://www.aclweb.org/anthology/S17-2058
DOI:
10.18653/v1/S17-2058
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/S17-2058.pdf