MCNN-LSTM: Combining CNN and LSTM to Classify Multi-Class Text in Imbalanced News Data

Author:

Hasib Khan Md1ORCID,Azam Sami2ORCID,Karim Asif2ORCID,Marouf Ahmed Al3ORCID,Shamrat F M Javed Mehedi4ORCID,Montaha Sidratul5ORCID,Yeo Kheng Cher2ORCID,Jonkman Mirjam2ORCID,Alhajj Reda3ORCID,Rokne Jon G.3ORCID

Affiliation:

1. Department of Computer Science and Engineering, Bangladesh University of Business and Technology, Dhaka, Bangladesh

2. Faculty of Science and Technology, Charles Darwin University, Casuarina, NT, Australia

3. Department of Computer Science, University of Calgary, Calgary, Canada

4. Department of Computer System and Technology, University of Malaya, Kuala Lumpur, Malaysia

5. Department of Computer Science and Engineering, Daffodil International University, Dhaka, Bangladesh

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

General Engineering,General Materials Science,General Computer Science,Electrical and Electronic Engineering

Reference58 articles.

1. Using bipartite graphs projected onto two dimensions for text classification;redmond;Proc 5th Int Conf Adv Comput Commun Inf Technol (CCIT),2017

2. BSIL: A Brain Storm-Based Framework for Imbalanced Text Classification

3. Power grid stability analysis using pipeline machine

4. Imbalanced text sentiment classification using universal and domain-specific knowledge

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