Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/329250
Title: | A Framework for Detection of SPAM in Social Media Networks using Machine Learning |
Researcher: | Y Padma |
Guide(s): | Y K Sundara Krishna |
Keywords: | Computer Science Computer Science Artificial Intelligence Engineering and Technology |
University: | Krishna University, Machilipatnam |
Completed Date: | 2021 |
Abstract: | newline With the growth in the communication systems, opinions became the most used communication method in the corporate, research and education. Public opinions and experience are important data in basic leadership handle. A few sites recommends clients to express their perspectives, recommendations and sentiments identified with administrations, polices, and so forth. With the improvement of web, individuals will probably express their perspectives and feelings on online business destinations, discussions and can interface seriously with the web. newline newline Item reviews created cooperatively by numerous web commentators can enable customers whether to buy or not and empower endeavours to enhance their business. This practice is known as Opinion/Review Spam, where spammers control for benefit or pick up. A number of researches are carried out in order to detect the spam messages by deploying the filters. The outcomes are satisfactory as most of the parallel works have demonstrated the rejection of the documents based on pre-defined keywords. In this work, the noticeable machine learning strategies that have been proposed to take care of the issue of survey spam discovery with the execution of various methodologies for grouping and location of survey spam. newline |
Pagination: | |
URI: | http://hdl.handle.net/10603/329250 |
Appears in Departments: | Computer Science |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01. title.pdf | Attached File | 116.36 kB | Adobe PDF | View/Open |
02. certificate & declaration.pdf | 131.42 kB | Adobe PDF | View/Open | |
04. contents.pdf | 524.48 kB | Adobe PDF | View/Open | |
07. chapter-1.pdf | 402.44 kB | Adobe PDF | View/Open | |
08. chapter-2.pdf | 499.65 kB | Adobe PDF | View/Open | |
09. chapter-3.pdf | 548.43 kB | Adobe PDF | View/Open | |
10. chapter-4.pdf | 301.66 kB | Adobe PDF | View/Open | |
11. chapter-5.pdf | 540.75 kB | Adobe PDF | View/Open | |
12. chapter-6.pdf | 672.3 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 208.29 kB | Adobe PDF | View/Open |
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