Megat Tharih Afendi, Megat Muazam YouTube spam classification using word frequencies. Project Report. Universiti Teknikal Malaysia Melaka, Melaka, Malaysia. (Submitted)
|
Text (Full Text)
YouTube spam classification using word frequencies.pdf - Submitted Version Download (2MB) | Preview |
Abstract
YouTube is among the largest websites and has been one of the Internet's most popular sites. Recognizing YouTube's features is indeed crucial for network activity and to sustainable development of this new service generation. Spam are seen as the most rapidly growth attacks that have infected lots of users all around the world especially in YouTube. In this study will be use YouTube spam collection data set that obtain from UCI Machine Learning Repository website which is this data are from among the 10 most viewed on the collection period and frequently use by past researcher. This dataset process through Bag-of-Word, Chi-Square, and Information Gain to propose SVM model that produce from this project. The objective of this project is to prove that SVM can provide result accuracy in detecting spam and ham comment on YouTube website. The project is giving hope to produce a system that can distinguish between spam and ham comment on web site methods based on SVM model.
| Item Type: | Final Year Project (Project Report) |
|---|---|
| Uncontrolled Keywords: | YouTube spam detection, SVM model, Bag-of-Words, Chi-Square, Information Gain |
| Subjects: | T Technology > T Technology (General) T Technology > TK Electrical engineering. Electronics Nuclear engineering |
| Divisions: | Library > Final Year Project > FTMK |
| Depositing User: | Sabariah Ismail |
| Date Deposited: | 23 Jun 2025 08:46 |
| Last Modified: | 23 Jun 2025 08:46 |
| URI: | http://digitalcollection.utem.edu.my/id/eprint/36124 |
Actions (login required)
 |
View Item |
Download Statistics
Download Statistics