A formal model for information selection in multi-sentence text extraction

  • Authors:
  • Elena Filatova;Vasileios Hatzivassiloglou

  • Affiliations:
  • Columbia University, New York, NY;Columbia University, New York, NY

  • Venue:
  • COLING '04 Proceedings of the 20th international conference on Computational Linguistics
  • Year:
  • 2004

Quantified Score

Hi-index 0.01

Visualization

Abstract

Selecting important information while accounting for repetitions is a hard task for both summarization and question answering. We propose a formal model that represents a collection of documents in a two-dimensional space of textual and conceptual units with an associated 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 provide approximation algorithms and empirically validate the performance of the proposed model when used with two very different sets of features, words and atomic events.