Retraining a spam detection model to handle new edge cases

Registration ID: IJNRD_193910

Published ID: IJNRD2305117

DOI: Click Here to Get

Mahalakshmi D

As the quality of online social networks has improved, spammers have discovered that they can easily exploit them to lure users to do undesirable things by posting spam comments on videos. In this project, spam detection has been done as well as consideration of YouTube comments. YouTube Bookmaker and Google Safe Browsing technologies both identify and filter spam. measures made by YouTube to fight spam. These programmes will block hazardous links, but they will not be able to protect the user as soon as possible in real time. As a result, companies and academics have developed a wide range of spam-free social networking systems. The survey to determine the most effective method of identifying spam comments has been completed. What we want is achieved by the bag-of-words paradigm, which translates the sentences or phrases and counts the occurrences of a comparable term. In the world of computer science, a "big" is a data structure that organised information similarly to a "array" or "list," except in this case, the order is meaningless and we simply keep track of the count rather than repeating it if an object occurs more than once.

Published Paper   E-Certificate

Mahalakshmi D (May-2023). Retraining a spam detection model to handle new edge cases. INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT, 8(5), b100-b105. https://ijnrd.org/papers/IJNRD2305117.pdf

Volume 8 Issue 5, May-2023

Pages : b100-b105

Paper Reg. ID: IJNRD_193910

Published Paper Id: IJNRD2305117

Downloads: 000121993

Research Area: Computer Engineering 

Country: Chennai, Tamil Nadu, India

Published Paper PDF: https://ijnrd.org/papers/IJNRD2305117.pdf

Published Paper URL: https://ijnrd.org/viewpaperforall?paper=IJNRD2305117

Journal Name: INTERNATIONAL JOURNAL OF NOVEL RESEARCH AND DEVELOPMENT(IJNRD)

ISSN: 2456-4184 | IMPACT FACTOR: 8.76 Calculated By Google Scholar | ESTD YEAR: 2016

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