Meet Notes

[s-m-quadri]

Cyberus Risk Measuring Paper Writing Workflow

• Literature Review = Problem in detail

  • Search for reasearh papers (at least 3-5):
    1. Find DOI number
    2. Goto https://www.sci-hub.se/
    3. Paste and check if it exists.
  • Read atleast abstract, introduction, conclusion.
  • (Optionally) Read methodology and results.
  • Write in your Literature review based on the information you gathered.

• Methodology = Your solution in detail

  • Already exists

• Results

  • Already exists

• Introduction

  • Build by yourself

• Conclusion

  • Build by yourself

• Abstract

  • Build by yourself

• Title

  • Build by yourself

Prompt

I have built a project for measuring risk, Cyberus. Ok. I have already written the methodology and results, but the literature review is missing. I'll provide you with some of the sections from the related research paper; you have to write two things.
1. Literature review based on that section with reference number
2. Maintain references with numbers
Note: Make sure to make it concise.
Are we set to go...

Research Paper Sample

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Our model has been trained using multiple classifiers to check and compare the results for greater accuracy. Each classifier will give its evaluated results to the user. After all the classifiers return its result to the user; then the user can compare it with other results to see whether the data is “spam” or “ham”. Each classifier result will be shown in graphs and tables for better understanding. The dataset is obtained from “Kaggle” website for training. The name of the dataset used is “spam.csv”. To test the trained machine, a different CSV file is developed with unseen data i.e. data which is not used for the training of the machine; named “emails.csv”. After the text edit has been completed, the paper is ready for the template. Duplicate the template file by using the Save As command, and use the naming convention prescribed by your conference for the name of your paper. In this newly created file, highlight all of the contents and import your prepared text file. You are now ready to style your paper; use the scroll down window on the left of the MS Word Formatting toolbar. Proceedings of the Second International Conference on Inventive Research in Computing Applications (ICIRCA-2020) IEEE Xplore Part Number: CFP20N67-ART; ISBN: 978-1-7281-5374-2 978-1-7281-5374-2/20/$31.00 ©2020 IEEE 112 Authorized licensed use limited to: Middlesex University. Downloaded on September 02,2020 at 11:32:18 UTC from IEEE Xplore. Restrictions apply. TABLE I. COMPARISION TABLE Classifiers Score 1 Score 2 Score 3 Score 4 1 Support Vector Classifier 0.81 0.92 0.95 0.92 2 K-Nearest Neighbour 0.92 0.88 0.87 0.88 3 Naïve Bayes 0.87 0.98 0.98 0.98 4 Decision Tree 0.94 0.95 0.93 0.95 5 Random Forest 0.90 0.92 0.92 0.92 6 AdaBoost Classifier 0.95 0.94 0.95 0.94 7 Bagging Classifier 0.94 0.94 0.95 0.94
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Kumar, N., Sonowal, S., & Nishant. (2020). Email Spam Detection Using Machine Learning Algorithms. 2020 Second International Conference on Inventive Research in Computing Applications (ICIRCA). doi:10.1109/icirca48905.2020.9183098