LearningToQuestion at SemEval 2017 Task 3: Ranking Similar Questions by Learning to Rank Using Rich Features

Naman Goyal


Abstract
This paper describes our official entry LearningToQuestion for SemEval 2017 task 3 community question answer, subtask B. The objective is to rerank questions obtained in web forum as per their similarity to original question. Our system uses pairwise learning to rank methods on rich set of hand designed and representation learning features. We use various semantic features that help our system to achieve promising results on the task. The system achieved second highest results on official metrics MAP and good results on other search metrics.
Anthology ID:
S17-2050
Volume:
Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017)
Month:
August
Year:
2017
Address:
Vancouver, Canada
Editors:
Steven Bethard, Marine Carpuat, Marianna Apidianaki, Saif M. Mohammad, Daniel Cer, David Jurgens
Venue:
SemEval
SIG:
SIGLEX
Publisher:
Association for Computational Linguistics
Note:
Pages:
310–314
Language:
URL:
https://aclanthology.org/S17-2050
DOI:
10.18653/v1/S17-2050
Bibkey:
Cite (ACL):
Naman Goyal. 2017. LearningToQuestion at SemEval 2017 Task 3: Ranking Similar Questions by Learning to Rank Using Rich Features. In Proceedings of the 11th International Workshop on Semantic Evaluation (SemEval-2017), pages 310–314, Vancouver, Canada. Association for Computational Linguistics.
Cite (Informal):
LearningToQuestion at SemEval 2017 Task 3: Ranking Similar Questions by Learning to Rank Using Rich Features (Goyal, SemEval 2017)
Copy Citation:
PDF:
https://aclanthology.org/S17-2050.pdf