HCCL at SemEval-2017 Task 2: Combining Multilingual Word Embeddings and Transliteration Model for Semantic Similarity
Junqing He, Long Wu, Xuemin Zhao, Yonghong Yan · 2017
In this paper, we introduce an approach to combining word embeddings and machine translation for multilingual semantic word similarity, the task2 of SemEval-2017.Thanks to the unsupervised transliteration model, our cross-lingual word embeddings encounter decreased sums of OOVs.Our results are produced using only monolingual Wikipedia corpora and a limited amount of sentence-aligned data.Although relatively little resources are utilized, our system ranked 3rd in the monolingual subtask and can be the 6th in the cross-lingual subtask.