HIERARCHICAL TEXT CLASSIFICATION USING DICTIONARY BASED APPROACH AND LONG-SHORT TERM MEMORY

Authors

  • Karishma D. Shaikh M. Tech. Student Department of Computer Science and Engg. Rajarambapu Institute of Technology, Sakharale, India.
  • Amol C. Adamuthe Assistant Professor, Dept. of Information Technology, Rajarambapu Institute of Technology, Sakharale, India

Keywords:

dictionary based approach, long-short term memory approach, preprocessing

Abstract

The text classification process has been well studied, but there are still many improvements in the classification and feature preparation, which can optimize the performance of classification for specific applications. In the paper we implemented dictionary based approach and long-short term memory approach. In the first approach, dictionaries will be padded based on field's specific input and use automation technology to expand. The second approach, long short term memory used word2vec technique. This will help us in getting a comprehensive pipeline of end-to-end implementations. This is useful for many applications, such as sorting emails which are spam or ham, classifying news as political or sports-related news, etc

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Published

2021-02-25

How to Cite

Karishma D. Shaikh, & Amol C. Adamuthe. (2021). HIERARCHICAL TEXT CLASSIFICATION USING DICTIONARY BASED APPROACH AND LONG-SHORT TERM MEMORY . JournalNX - A Multidisciplinary Peer Reviewed Journal, 100–105. Retrieved from https://repo.journalnx.com/index.php/nx/article/view/2320

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