The application of the connectionist method of semantic similarity for kazakh language

被引：0

作者：

Kalimoldayev, Maksat N. ^{[1
]}

Koibagarov, Kairat Ch. ^{[1
]}

Pak, Alexandr A. ^{[1
]}

Zharmagambetov, Arman S. ^{[2
]}

机构：

[1] Inst ICT, Alma Ata, Kazakhstan

[2] LLC AlemRes, Alma Ata, Kazakhstan

来源：

2015 TWELVE INTERNATIONAL CONFERENCE ON ELECTRONICS COMPUTER AND COMPUTATION (ICECCO) | 2015年

关键词：

natural language processing; neural networks; semantic similarity;

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：

The unsupervised algorithm for the calculation of semantic similarity are essential in many areas of modern natural language processing. One of the most promising methods for the calculation of semantic similarity is neural network algorithm "word2vec. This method has been tested for most European languages, namely English, German, French and Russian. This paper presents the results of numerical experiments for synthetic agglutinative Kazakh language, which has a number of features and differences from all the above languages.

引用

页码：60 / 62

页数：3