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http://hdl.handle.net/20.500.11861/7428| Title: | SUNNYNLP at SemEval-2018 Task 10: A Support-Vector-Machine-Based Method for Detecting Semantic Difference using Taxonomy and Word Embedding Features |
| Authors: | Lai, Sunny Prof. LEUNG Kwong Sak Leung, Yee |
| Issue Date: | 2018 |
| Source: | NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop pp. 741-746 |
| Conference: | NAACL HLT 2018 - International Workshop on Semantic Evaluation, SemEval 2018 - Proceedings of the 12th Workshop |
| Abstract: | We present SUNNYNLP, our system for solving SemEval 2018 Task 10: “Capturing Discriminative Attributes”. Our Support-Vector-Machine(SVM)-based system combines features extracted from pre-trained embeddings and statistical information from Is-A taxonomy to detect semantic difference of concepts pairs. Our system is demonstrated to be effective in detecting semantic difference and is ranked 1st in the competition in terms of F1 measure. The open source of our code is coined SUNNYNLP. © 2018 Association for Computational Linguistics |
| Type: | Conference Paper |
| URI: | http://hdl.handle.net/20.500.11861/7428 |
| ISBN: | 978-194808720-9 |
| Appears in Collections: | Applied Data Science - Publication |
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