AUTOMATIC KEYWORD EXTRACTION USING ARTIFICIAL NEURAL NETWORK AND FEATURE EXTRACTION

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Authors

  • Nguyen Van Son (Corresponding Author) Military Information Technology Institute, Academy of Military Science and Technology

Keywords:

Feature extraction; Keyword extraction; Artificial neural network; Supervised learning.

Abstract

Extracting keywords from documents is an essential task in natural language processing. A challenge of this task is to define a reasonable set of keywords from which we can find all relevant documents. This paper proposes a new approach that exploits word-level handcrafted features and machine learning models to select a single document's most important keywords. To evaluate the proposed solution, we compare our results with the latest supervised and unsupervised automatic keyword extraction methods. Experiment results show that our model achieves the best results on the 9/20 data corpus. It points out that our proposed approach is promising.

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Published

16-11-2020

How to Cite

Son. “AUTOMATIC KEYWORD EXTRACTION USING ARTIFICIAL NEURAL NETWORK AND FEATURE EXTRACTION”. Journal of Military Science and Technology, no. 69A, Nov. 2020, pp. 63-74, https://online.jmst.info/index.php/jmst/article/view/132.

Issue

Section

Research Articles

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