Browsing by Author Trieu, Hai-Long

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  • Authors: Trieu, Hai-Long; Nguyen, Phuong-Thai; Nguyen, Le-Minh (2015)

  • The sentence alignment approach proposed by Moore, 2002 (M-Align) is an effective method which gets a rela-tively high performance based on mbination of length-based and word correspondences. Nevertheless, despite the high precision, M-Align usually gets a low recall especially when dealing with sparse data problem. We pro-pose an algorithm which not only exploits advantages of M-Align but overcomes the weakness of this baseline method by using a new feature in sentence alignment, word clustering. Experiments shows an mprovement on the baseline method up to 30% recall while precision is reasonable.

Browsing by Author Trieu, Hai-Long

Jump to: 0-9 A B C D E F G H I J K L M N O P Q R S T U V W X Y Z
or enter first few letters:  
Showing results 1 to 1 of 1
  • document.pdf.jpg
  • Article


  • Authors: Trieu, Hai-Long; Nguyen, Phuong-Thai; Nguyen, Le-Minh (2015)

  • The sentence alignment approach proposed by Moore, 2002 (M-Align) is an effective method which gets a rela-tively high performance based on mbination of length-based and word correspondences. Nevertheless, despite the high precision, M-Align usually gets a low recall especially when dealing with sparse data problem. We pro-pose an algorithm which not only exploits advantages of M-Align but overcomes the weakness of this baseline method by using a new feature in sentence alignment, word clustering. Experiments shows an mprovement on the baseline method up to 30% recall while precision is reasonable.