Topic themes for multi-document summarisation

Harabagiu, S., & Lacatusu, F. (2005). Topic themes for multi-document summarisation. In Proceedings of the 28th annual international ACM-SIGIR conference on research and development in information retrieval (SIGIR 2005) (pp. 202–209).
ABSTRACT
Most approaches to extractive summarization define a set of features upon which selection of sentences is based, using algorithms independent of the features themselves. We propose a new set of features based on low-level, atomic events that describe relationships between important actors in a document or set of documents. We investigate the effect this new feature has on extractive summarization, compared with a baseline feature set consisting of the words in the input documents, and with state-of-the-art summarization systems. Our experimental results indicate that not only the event-based features offer an improvement in summary quality over words as features, but that this effect is more pronounced for more sophisticated summarization methods that avoid redundancy in the output.