Paper: A Formal Model For Information Selection In Multi-Sentence Text Extraction

ACL ID C04-1057
Title A Formal Model For Information Selection In Multi-Sentence Text Extraction
Venue International Conference on Computational Linguistics
Session Main Conference
Year 2004
Authors

Selecting important information while account- ing for repetitions is a hard task for both sum- marization and question answering. We pro- pose a formal model that represents a collec- tion of documents in a two-dimensional space of textual and conceptual units with an asso- ciated mapping between these two dimensions. This representation is then used to describe the task of selecting textual units for a summary or answer as a formal optimization task. We pro- vide approximation algorithms and empirically validate the performance of the proposed model when used with two very different sets of fea- tures, words and atomic events.