Neobility at SemEval-2017 Task 1: An Attention-based Sentence Similarity Model
Shan-Si Elementary School（山寺小学）；University of Washington（华盛顿大学）
英文摘要：
This paper describes a neural-network model which performed competitively (top 6) at the SemEval 2017 cross-lingual Semantic Textual Similarity (STS) task. Our system employs an attention-based recurrent neural network model that optimizes the sentence similarity. In this paper, we describe our participation in the multilingual STS task which measures similarity across English, Spanish, and Arabic.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
