Please use this identifier to cite or link to this item: http://repository.vnu.edu.vn/handle/VNU_123/60587
Title: Paraphrase Identification in Vietnamese Documents
Authors: Ngo, Xuan Bach
Tran, Thi Oanh
Nguyen, Trung Hai
Tu, Minh Phuong
Keywords: K-Nearest Neighbor;Paraphrase Identification;Semantic Similarity;Support Vector Machines;Maximum Entropy Model;Naive Bayes Classification
Issue Date: 2015
Publisher: IEEE
Abstract: In this paper, we investigate the task of paraphrase identification in Vietnamese documents, which identify whether two sentences have the same meaning. This task has been shown to be an important research dimension with practical applications in natural language processing and data mining. We choose to model the task as a classification problem and explore different types of features to represent sentences. We also introduce a paraphrase corpus for Vietnamese, vnPara, which consists of 3000 Vietnamese sentence pairs. We describe a series of experiments using various linguistic features and different machine learning algorithms, including Support Vector Machines, Maximum Entropy Model, Naive Bayes, and k-Nearest Neighbors. The results are promising with the best model achieving up to 90% accuracy. To the best of our knowledge, this is the first attempt to solve the task of paraphrase identification for Vietnamese.
Description: Knowledge and Systems Engineering (KSE), 2015 Seventh International Conference on
URI: http://repository.vnu.edu.vn/handle/VNU_123/60587
Appears in Collections:IS - Papers

Files in This Item:
Thumbnail

  • File : Paraphrase Identification in Vietnamese Documents.PDF
  • Description : 
  • Size : 261.95 kB
  • Format : Adobe PDF


  • Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.