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Browsing Proceedings by Subject "Sentiment analysis"

Browsing Proceedings by Subject "Sentiment analysis"

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  • An Aspect of Sentiment Analysis: Sentimental Noun with Dual Sentimental Words Analysis 
    Chaki, Prosanta Kumar; Hossain, Ikrum; Chanda, Probhas Ranjan; Anirban, Shikha (IEEE, 2018-09-06)
    With the increasing number of digital data and new technologies, business trends and model are becoming more dependent on computer science for making business decision and operation. By extracting user opinion for decision ...
  • Machine learning based class level prediction of restaurant reviews 
    Hossain, F. M. Takbir; Hossain, Md. Ismail; Nawshin, Samia (IEEE, 2018-02-12)
    Nowadays with the proliferation of location aware technologies and smart phones people tend to give reviews for all types of products services and place them online. It is very important to extract knowledge or information ...
  • Sentiment Analysis of Tweet Data: The Study of Sentimental State of Human from Tweet Text 
    Chowdhury, S. M. Mazharul Hoque; Ghosh, Priyanka; Abujar, Sheikh; Afrin, Most. Arina; Hossain, Syed Akhter (Springer Nature Singapore Pte Ltd., 2018-09-02)
    Sentiment analysis is a hot topic today. The purpose of this research is finding out sentimental state of a person or a group of people using data mining. The target of this research is building a user friendly interface ...
  • Sentiment Extraction From Bangla Text: A Character Level Supervised Recurrent Neural Network Approach 
    Haydar, Mohammad Salman; Helal, Mustakim Al; Hossain, Syed Akhter (International Conference on Computer, Communication, Chemical, Material and Electronic Engineering, 2018-09-20)
    Over the recent years, people are heavily getting involved in the virtual world to express their opinions and feelings. Each second, hundreds of thousands of data are being gathered in the social media sites. Extraction ...
  • State-of-the-Art Review on Opinion Mining from Online Customers’ Feedback 
    Bhuiyan, Touhid; Xu, Yue; Josang, Audun (Proceedings of the 9th Asia-Pacific Complex Systems Conference, 2009)
    Dealing with the ever-growing information overload in the Internet, Recommender Systems are widely used online to suggest potential customers item they may like or find useful. Collaborative Filtering is the most popular ...

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