A method for automatic detection of acronyms in texts and building a dataset for acronym disambiguation

被引：3
|
作者：
Azimi, Sasan [1 ]
Veisi, Hadi [1 ]
Amouie, Reyhaneh [1 ]
机构：
[1] Univ Tehran, Tehran, Iran
来源：
2019 5TH IRANIAN CONFERENCE ON SIGNAL PROCESSING AND INTELLIGENT SYSTEMS (ICSPIS 2019) | 2019年
关键词：
Acronym disambiguation; Tech-mining; Text Mining; Natural Language Processing;
D O I：
10.1109/icspis48872.2019.9066084
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
Nowadays, there is an increasing tendency for using acronyms in technical texts, which has led to ambiguous acronyms with different possible expansions. Diversity of expansions of a single acronym makes recognizing its expansion a challenging task. Replacing acronyms with incorrect expansions will lead to problems in text mining procedures, namely text normalization, summarization, machine translation, and tech-mining. Tech-mining involves exploring and analyzing technical texts to recognize the relations between technologies. This paper is aimed at proposing a method for building a dataset that meets the requirements for training acronym disambiguation models in technical texts. In this paper, challenges in automatic acronym disambiguation are presented. We have proposed a method for building the dataset and the accuracy of the acronym disambiguation model is 86%.
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收藏
页数：4
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