Detection and Classification of Advertisements Using Machine Learning Approach


  • Varagiri Shailaja, Kunuku Anusha Nagina, Bharathi Panduri, K V Sharada, Sreethi Musunuru


This paper evaluates and tries to create video ads being shown more related to the material of video has been viewed. Ads could be prepared more accurate depending upon the attention of user. Hence the ideal suggestion of the advertisements depends on the information based on visualization of video seen by consumer that can be viewed by the great deals for the marketer and the customer to enhance the product sales. Categorization based on the attributes we assume that we already have the data of customer visualization. Now these characteristics are attempted and matched with the material of the video so that these video advertisements will be viewed as text and stored in a file, which we evaluate by utilizing SVM and Naive bayes algorithms. Hence the proposed method in this paper provides a technique that how we can acknowledge the intent of advertisement.