TIIS (한국인터넷정보학회)
Current Result Document :
| 한글제목(Korean Title) |
Lightweight Named Entity Extraction for Korean Short Message Service Text |
| 영문제목(English Title) |
Lightweight Named Entity Extraction for Korean Short Message Service Text |
| 저자(Author) |
Choong-Nyoung Seon
JinHwan Yoo
Harksoo Kim
Ji-Hwan Kim1
Jungyun Seo
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| 원문수록처(Citation) |
VOL 05 NO. 03 PP. 0560 ~ 0574 (2011. 03) |
한글내용
(Korean Abstract) |
|
영문내용
(English Abstract) |
In this paper, we propose a hybrid method of Machine Learning (ML) algorithm and a rule-based algorithm to implement a lightweight Named Entity (NE) extraction system for Korean SMS text. NE extraction from Korean SMS text is a challenging theme due to the resource limitation on a mobile phone, corruptions in input text, need for extension to include personal information stored in a mobile phone, and sparsity of training data. The proposed hybrid method retaining the advantages of statistical ML and rule-based algorithms provides fully-automated procedures for the combination of ML approaches and their correction rules using a threshold-based soft decision function. The proposed method is applied to Korean SMS texts to extract person’s names as well as location names which are key information in personal appointment management system. Our proposed system achieved 80.53% in F-measure in this domain, superior to those of the conventional ML approaches. |
| 키워드(Keyword) |
Named entity (NE) extraction
machine learning (ML)
rule-based
lightweight
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| 파일첨부 |
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