Text summarization: An old challenge and new approaches

Abstract

One of the most relevant todays problems called information overloading has increased the necessity of more sophisticated and powerful information compression methods - summarizers. This chapter firstly introduces a taxonomy of summarization methods, an overview of their principles from classical ones, over corpus based, to knowledge rich approaches. We consider various aspects which can affect their categorization. A special attention is devoted to application of recent information reduction methods, based on algebraic transformations. Our own LSA (Latent Semantic Analysis) based approach is included too. The next part is devoted to evaluation measures for assessing quality of a summary. The taxonomy of evaluation measures is presented and their features are discussed. Further, we introduce experiences with the development of our web searching and summarization system. Finally, some new ideas and a conception for the future of this field are mentioned. © 2009 Springer-Verlag Berlin Heidelberg.