QLUT at SemEval-2017 Task 2: Word Similarity Based on Word Embedding and Knowledge Base

Fanqing Meng, Wenpeng Lu*, Yuteng Zhang, Ping Jian, Shumin Shi, Heyan Huang

*此作品的通讯作者

科研成果: 书/报告/会议事项章节会议稿件同行评审

5 引用 (Scopus)

摘要

This paper shows the details of our system submissions in the task 2 of SemEval 2017. We take part in the subtask 1 of this task, which is an English monolingual subtask. This task is designed to evaluate the semantic word similarity of two linguistic items. The results of runs are assessed by standard Pearson and Spearman correlation, contrast with official gold standard set. The best performance of our runs is 0.781 (Final). The techniques of our runs mainly make use of the word embeddings and the knowledge-based method. The results demonstrate that the combined method is effective for the computation of word similarity, while the word embeddings and the knowledge-based technique, respectively, needs more deeply improvement in details.

源语言英语
主期刊名ACL 2017 - 11th International Workshop on Semantic Evaluations, SemEval 2017, Proceedings of the Workshop
出版商Association for Computational Linguistics (ACL)
235-238
页数4
ISBN(电子版)9781945626555
出版状态已出版 - 2017
活动11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017 - Vancouver, 加拿大
期限: 3 8月 20174 8月 2017

出版系列

姓名Proceedings of the Annual Meeting of the Association for Computational Linguistics
ISSN(印刷版)0736-587X

会议

会议11th International Workshop on Semantic Evaluations, SemEval 2017, co-located with the 55th Annual Meeting of the Association for Computational Linguistics, ACL 2017
国家/地区加拿大
Vancouver
时期3/08/174/08/17

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