From Treebank Conversion to Automatic Dependency Parsing for Vietnamese

Nguyen, Dat Quoc; Nguyen, Dai Quoc; Pham, Son Bao; Nguyen, Phuong-Thai; Nguyen, Minh Le

doi:10.1007/978-3-319-07983-7_26

Cited by 37 publications

(52 citation statements)

References 13 publications

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“…In the future, we will extend the question analysis module by using other additional features based on the dependency tree [11]. We will also expand the database to be able to deal with a wide range of questions and improve the answer selection module.…”

Section: Resultsmentioning

confidence: 98%

A Community-Based Vietnamese Question Answering System

Tran

Nguyen

Duc

et al. 2015

Advances in Intelligent Systems and Computing

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Abstract. Most recent Vietnamese QA systems have not considered so far in using the data crawled from the community web services as a useful resource. In this paper, we take into accounts the community-based resource to build a Vietnamese question answering system named VnCQAs. Our system comprises of three modules for building the database of question-answer pairs, analyzing questions and choosing the best answer respectively. Experimental results show that our system achieves promising performances.

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Section: Resultsmentioning

confidence: 98%

A Community-Based Vietnamese Question Answering System

Tran

Nguyen

Duc

et al. 2015

Advances in Intelligent Systems and Computing

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“…We use the dependency tree to find keywords on the premise that is to identify a word as informative or not, we take into account the relationships of that word with other words in the question by using the Vietnamese dependency parser [14]. For each question, the dependency parser creates a tree that contains the tree structure, the relation of the words and several other information such as part-of-speech tag (as shown in Figure 4, the question is "How do I delete messages in Iphone?").…”

Section: Methodsmentioning

confidence: 99%

Question Analysis for a Community-Based Vietnamese Question Answering System

Tran

Nguyen

Pham

2015

Advances in Intelligent Systems and Computing

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Abstract. This paper describes the approach for analyzing questions in our community-based Vietnamese question answering system (VnCQAs), in which we focus on two subtasks: question classification and keyword identification. The question classification employs the machine learning approaches with a feature which represents a measure of similarity between two questions, while the keyword identification uses the dependency-tree-based features. Experimental results are promising, in which the question classification obtains the accuracy of 95.7% and the keyword identification gains the accuracy of 85.8%. Furthermore, these two subtasks help to improve the accuracy for finding the similar questions in our VnCQAs by 6.75%.

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“…For Vietnamese dependency parsing, there have been many contributions [6,7,10,15,17]. In 2008, Nguyễn Lê Minh et al [7] used MST parser on a corpus consisting of 450 sentences.…”

Section: Introductionmentioning

confidence: 99%

“…In 2012, Lê Hồng Phương et al [10] used a lexicalized tree-adjoining grammar parser trained on a subset of the Vietnamese treebank. In 2014, Nguyen et al [17] used MaltParser and MSTParser on a Vietnamese dependency treebank which is converted automatically from a Vietnamese treebank. In 2015, Lê Hồng Phương et al improved accuracy of Vietnamese dependency parsing, used distributed word representations with Skip-gram and GloVe model [6,15] for transition-based dependency parsing.…”

Section: Introductionmentioning

confidence: 99%