@inproceedings{74e20fb47ef04b96bf33205638bbfcf5,
title = "Polytope model for extractive summarization",
abstract = "The problem of text summarization for a collection of documents is defined as the problem of selecting a small subset of sentences so that the contents and meaning of the original document set are preserved in the best possible way. In this paper we present a linear model for the problem of text summarization, where we strive to obtain a summary that preserves the information coverage as much as possible in comparison to the original document set. We construct a system of linear inequalities that describes the given document set and its possible summaries and translate the problem of finding the best summary to the problem of finding the point on a convex polytope closest to the given hyperplane. This re-formulated problem can be solved efficiently with the help of quadratic programming.",
keywords = "Polytope model, Quadratic programming, Text summarization",
author = "Marina Litvak and Natalia Vanetik",
year = "2012",
month = dec,
day = "1",
language = "English",
isbn = "9789898565297",
series = "KDIR 2012 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval",
pages = "281--286",
booktitle = "KDIR 2012 - Proceedings of the International Conference on Knowledge Discovery and Information Retrieval",
note = "4th International Conference on Knowledge Discovery and Information Retrieval, KDIR 2012 ; Conference date: 04-10-2012 Through 07-10-2012",
}