Talla At SemEval-2017 Task 3: Identifying Similar Questions through Paraphrase Detection
Abstract
This paper describes our approach to the SemEval-2017 shared task of determining question-question similarity in a community question-answering setting (Task 3B). We extracted both syntactic and semantic similarity features between candidate questions, performed pairwise-preference learning to optimize for ranking order, and then trained a random forest classifier to predict whether the candidate questions were paraphrases of each other. This approach achieved a MAP of 45.7% out of max achievable 67.0% on the test set.
Recommended Citation
Galbraith, B., Pratap, B., & Shank, D. B. (2017). Talla At SemEval-2017 Task 3: Identifying Similar Questions through Paraphrase Detection. Proceedings of the 11th International Workshop on Semantic Evaluation (2017, Vancouver, Canada), pp. 375-379.
The definitive version is available at https://doi.org/10.18653/v1/S17-2062
Meeting Name
11th International Workshop on Semantic Evaluation, SemEval@ACL 2017 (2017: Aug. 3-4, Vancouver, Canada)
Department(s)
Psychological Science
Document Type
Article - Conference proceedings
Document Version
Citation
File Type
text
Language(s)
English
Publication Date
01 Aug 2017
