Improving keyword extraction from movie subtitles by utilizing temporal properties

Abstract

In our work we aim at keyword extraction from movie subtitles. Keywords and key phrases although missing the context can be found very helpful in finding, understanding, organizing and recommending the media content. Generally, they are used by search engines to help find the relevant information. Movies and video content are becoming massively available and widespread. The ability to automatically describe and classify videos has a vast domain of application. In our work we select movie subtitles as a source of information to process. We proposed a method for keyword extraction from movie subtitles by analysing their temporal properties and detecting conversations. We evaluated our method by conducting two experiments (a priori synthetic experiment and a posteriori user experiment) involving 200 movies and show that conversation analysis can improve traditional approaches based on automatic term extraction algorithms.