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International Journal of Engineering and Applied Physics
Number of Followers: 0  

  This is an Open Access Journal Open Access journal
ISSN (Online) 2737-8071
Published by IJEAP Homepage  [1 journal]
  • Analysis of User’s Opinion using Deep Neural Network Techniques

    • Authors: Harini
      Abstract: Through many research and discoveries it has been widely accepted that aspect-level sentiment classification is achieved effectively by using Long Short-Term Memory (LSTM) network combined with attention mechanism and memory module. As existing approaches widely depend on the modelling of semantic relatedness of an aspect, at the same time we ignore their syntactic dependencies which is already a part of that sentence. This will result in undesirably an aspect on textual words that are descriptive of other aspects. So, in this paper, to offer syntax free contexts as well as they should be aspect specific, so we propose a proximity-weighted convolution network. To be more precise, we have one way of determining proximity weight which is dependency proximity. The construction of the model includes a bidirectional LSTM architecture along with a proximity-weighted convolution neural network.
      Issue No: Vol. 1, No. 1
       
  • Naive Bayes machine learning approach for discovery of Spam Comment in
           YouTube station

    • Authors: Sohom Bhattacharya, Shubham Bhattacharjee, Anup Das, Anirban Mitra , Ishita Bhattacharya , Subir Gupta
      Abstract: In the 21st Century, web-based media assumes an indispensable part in the interaction and communication of civilization. As an illustration of web-based media viz. YouTube, Facebook, Twitter, etc., can increase the social regard of a person just as a gathering. Yet, every innovation has its pros as well as cons. In some YouTube channels, a machine-made spam remark is produced on that recordings, moreover, a few phony clients additionally remark a spam comment which creates an adverse effect on that YouTube channel.  The spam remarks can be distinguished by using AI (artificial intelligence) which is based on different Algorithms namely Naive Bayes, SVM, Random Forest, ANN, etc. The present investigation is focussed on a machine learning-based Naive Bayes classifier ordered methodology for the identification of spam remarks on youtube.  
      Issue No: Vol. 1, No. 1
       
  • Machine Learning-based Linear regression way to deal with making data
           science model for checking the sufficiency of night curfew in Maharashtra,
           India

    • Authors: Subham Panda, Ayan Kumar Ghosh, Anup Das, Uttam Dey, Subir Gupta
      Abstract: The birthplace of the novel Covid-19 sickness or COVID-19 began its spread around Wuhan city, China. The spread of this novel infection sickness began toward the start of December 2019. The Covid-19 illness spreads from one individual to another through hacking, sniffling, etc. To stop the spreading of the novel Covid-19 infection the distinctive nation has presented diverse strategies. Some regularly utilized methods are lockdown, night curfew, etc. The fundamental intention of the systems was to stop the social events and leaving homes without serious issues. Utilizing a diverse system Covid-19 first stage can address for saving individuals. Presently the second influx of this novel Covid illness has begun its top from the mid of April-May. The second convergence of this novel Covid disorder flooded all through the world and in India too. To stop the spread of this novel Covid sickness India's richest state Maharashtra government constrained the decision of night curfew. In this paper, we are taking as a relevant examination the night curfew on a schedule of Maharashtra. Here, we study that this system may or may not be able to stop the spread of pandemics. We are using the Machine learning(ML) approach to managing regulate study this case. ML has various systems yet among all of those here we use Linear Regression for the current circumstance. The reproduced insight that readies the plan orchestrated to learn with no other person. Linear Regression is the affirmed strategy for looking over the connection between two sections. Between the two segments, one is astute and another is a seen variable.
      Issue No: Vol. 1, No. 1
       
 
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