Evaluation of video news classification techniques for automatic content personalisation
Marcelo Garcia Manzato, Alessandra Alaniz Macedo, Rudinei Goularte · International Journal of Advanced Media and Communication · 2009
Personalisation tasks require the use of semantic information, extracted from multimedia streams, in order to achieve the benefits of automatic matching user preferences with multimedia content meaning. Text-based classification techniques may be used in closed-captions captured from news programmes, which can define the subject of each piece of news. Latent Semantic Indexing (LSI)-based systems are widely used for information retrieval purposes, and may be adapted to classification tasks; however, some drawbacks of the technique may impose limitations, mainly when considering multiple collections. In this paper, we compare an LSI implementation with a Genetic Algorithm (GA)-based system which was designed with the same objective. We show that the GA alternative achieves better results when used to automatically classify pieces of news video programmes.