Video Classification into Academic and Entertainment using Subtitles

Abstract

Automated classification of text into predefined categories has always been considered as a vital method to manage and process a vast amount of documents in digital forms that are widespread and continuously increasing. This kind of web information is popularly known as the digital/electronic information. It is in the form of documents, conference material, publications, journals, editorials, web pages, videos, e mail etc. People largely access information from these online sources rather than being limited to archaic paper sources like books, magazines, newspapers etc. But the main problem is that this enormous information lacks organization which makes it difficult to manage. Text classification is recognized as one of the key techniques used for organizing such kind of digital data. This paper describes our work on building a Classification system for video subtitles. As an example, we report on our evaluation results for two TV genres ­Academic and Entertainment. Through this implementation, the user can classify the videos into academic and entertainment in any software or system, which will help the user to differentiate the videos properly into useful and distracting content. This enables applications like social networking and instant messaging apps to filter distracting content, thereby enhancing productivity of users.