Please use this identifier to cite or link to this item: 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
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