Semantic Video Classification Based on Subtitles and Domain Terminologies

In this paper we explore an unsupervised approach to classify video content by analyzing the corresponding subtitles. The proposed method is based on the WordNet lexical database and the WordNet domains and applies natural language processing techniques on video subtitles. The method is divided into several steps. The first step includes subtitle text preprocessing. During the next steps, a keyword extraction method and a word sense disambiguation technique are applied. Subsequently, the WordNet domains that correspond to the correct word senses are identified. The final step assigns category labels to the video content based on the extracted domains. Experimental results with documentary videos show that the proposed method is quite effective in discovering the correct category for each video. Key words: video classification, text classification, WordNet domains

• Type: Conference
• Year: 2007
• Where: SAMT
• Authors: Polyxeni Katsiouli, Vassileios Tsetsos, Stathes Hadjiefthymiades
• Keywords: SAMT 2007, Video Content, WordNet Domains, WordNet Lexical Database