Named Entity Recognition for Vietnamese

Nguyen, Dat Ba; Hoang, Son Huu; Pham, Son Bao; Nguyen, Thi-Hoai-Thu

doi:10.1007/978-3-642-12101-2_22

Cited by 16 publications

(9 citation statements)

References 7 publications

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“…Used algorithms include rule-based (Vo and Ock, 2012), support vector machine (SVM; Tran et al, 2007) and conditional random field (Nguyen et al, 2005;Pham et al, 2012;Sam et al, 2011). Some other researches focus on corpus building Nguyen et al, 2010). Unfortunately, none of those research has resulted in a free/open-source software.…”

Section: Named-entity Recognitionmentioning

confidence: 97%

VNLP

Le¹,

Ngoc²,

Nguyen³

et al. 2013

Proceedings of the Fourth Symposium on Information and Communication Technology - SoICT '13

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Natural Language Processing (NLP) for Vietnamese has been researched for more than a decade but still lacks of an opensource NLP pipeline. As the result, researchers have to spend a lot of time on various fundamental tasks before working on the task of interest. Besides, the circumstance holds back text processing technology in Vietnam because an application costs much more money and time to reach a deliverable state. This work is an attempt to solve this issue. By incorporating available open-source software packages and implementing new ones, we have created an opensource, production-ready solution for Vietnamese text processing. Via three experiments, we demonstrated its effectiveness and efficiency. The software has helped us to develop our solution for Vietnamese sentiment analysis and online reputation management and we hope that it will also facilitate research in Vietnamese NLP.

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Section: Named-entity Recognitionmentioning

confidence: 97%

VNLP

Le¹,

Ngoc²,

Nguyen³

et al. 2013

Proceedings of the Fourth Symposium on Information and Communication Technology - SoICT '13

View full text Add to dashboard Cite

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“…or using gazetteers [8]. Up to now, there are many studies using this method [9], [10] or [11] that obtain high performance including tasks for Vietnamese [2], [3].…”

Section: Related Workmentioning

confidence: 99%

Information Extraction for Vietnamese Real Estate Advertisements

Pham¹,

Pham

2012

2012 Fourth International Conference on Knowledge and Systems Engineering

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Advertising has appeared in almost all areas of life. The large number of advertisements, especially in real estate domain, has raised a need for an effective way to search and find useful information for users. In this paper, we propose a rule-based approach to build an Information Extraction system for Vietnamese online real estate advertisements. Experimental results shows that our approach is very promising with an overall F-measure of 91% on a collection of data collected from popular Vietnamese real estate websites.

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“…Some other works proposed a rule-based method [16], employed bootstrapping algorithm and a rule-based model [24], combined linguistically motivated and ontological features [17] for NER.…”

Section: Related Workmentioning

confidence: 99%

Named Entity Recognition in Vietnamese Tweets

Nguyen

Snášel

2015

Computational Social Networks

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Abstract. Named entity recognition (NER) is a task of detecting named entities in documents and categorizing them to predefined classes such as Person (PER), Location (LOC), Organization (ORG) and so on. There have been many approaches proposed to tackle this problem in both formal texts such as news or authorized web content and short texts such as contents in online social network. However, those texts were written in languages other than Vietnamese. In this paper, we propose a method for NER in Vietnamese tweets. Since tweets on Twitter are noisy, irregular, short and consist of acronyms, spelling errors, NER in those tweets is a challenging task. Our method firstly normalizes tweets and then applies a learning model to recognize named entities using six different types of features. We built a training set of more than 40,000 named entities, and a testing set of 2,446 named entities to evaluate our system. The experiment results show that our system achieves encouraging performance with 82.3% F1 score.

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Named Entity Recognition for Vietnamese

Cited by 16 publications

References 7 publications

VNLP

VNLP

Information Extraction for Vietnamese Real Estate Advertisements

Named Entity Recognition in Vietnamese Tweets

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