Sense Inventories for Arabic Texts

被引:0
|
作者
Alian, Marwah [1 ]
Awajan, Arafat [1 ,2 ]
机构
[1] Princess Sumaya Univ Technol, Amman, Jordan
[2] Mutah Univ, Mutah, Jordan
来源
2020 21ST INTERNATIONAL ARAB CONFERENCE ON INFORMATION TECHNOLOGY (ACIT) | 2020年
关键词
Word sense induction; Word sense disambiguation; Arabic text; sense inventory;
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Word sense disambiguation is the process of determining the proper meaning of a word according to its context. In this study, we represent the impact of word embedding on building Arabic sense inventory by an unsupervised approach. Three pre-trained embeddings are tested to investigate their effect on the resulting sense inventory and their efficiency in word sense disambiguation for Arabic context. Sense inventories are constructed using a fully unsupervised method based on graph-based word sense induction algorithm. The results show that Aravec-Twitter inventory achieves the best accuracy of 0.47 for 50-neighbors and a close accuracy to the Fasttext inventory for 200-neighbors.
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页数:4
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