Comparative study of CNN and LSTM for opinion mining in long text

• Autorzy: Yousf Siham , Rhanoui Maryem , Mounia Mikram

Identyfikatory

DOI

10.14313/JAMRIS/3-2020/34

• Języki publikacji: EN

Abstrakty

EN

The digital revolution has encouraged many companies to set up new strategic and operational mechanisms to supervise the flow of information published about them on the Web. Press coverage analysis is a part of sentiment analysis that allows companies to discover the opinion of the media concerning their activities, products and services. It is an important research area, since it involves the opinion of informed public such as journalists, who may influence the opinion of their readers. However, from an implementation perspective, the analysis of the opinion from media coverage encounters many challenges. In fact, unlike social networks, the Media coverage is a set of large textual documents written in natural language. The training base being huge, it is necessary to adopt large-scale processing techniques like Deep Learning to analyze their content. To guide researchers to choose between one of the most commonly used models CNN and LSTM, we compare and apply both models for opinion mining from long text documents using real datasets.

Słowa kluczowe

EN

deep learning; long text opinion mining; CNN; LSTM

• Wydawca: Łukasiewicz Industrial Research Institute for Automation and Measurements PIAP
• Czasopismo: Journal of Automation Mobile Robotics and Intelligent Systems
• Rocznik: 2020
• Tom: Vol. 14, No. 3
• Strony: 50--55
• Opis fizyczny: Bibliogr. 23 poz., rys.

Twórcy

autor

Yousf Siham

• SIP Research Team, Rabat IT Center, Mohammed V University in Rabat, Rabat, Morocco
• Meridian Team, LYRICA Laboratory, School of Information Sciences, Rabat, Morocco

autor

Rhanoui Maryem

• IMS Team, ADMIR Laboratory, Rabat IT Center, ENSIAS, Mohammed V University in Rabat, Morocco
• Meridian Team, LYRICA Laboratory, School of Information Sciences, Rabat, Morocco

autor

Mounia Mikram

• LRIT, Faculty of Science, Mohammed V University in Rabat, Rabat, Morocco
• Meridian Team, LYRICA Laboratory, School of Information Sciences, Rabat, Morocco

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