Graph-based Ranking Algorithms for Sentence Extraction, Applied to Text Summarization

Description:

Abstract: This paper presents an innovative unsupervised method for automatic sentence extraction using graph-based ranking algorithms. We evaluate the method in the context of a text summarization task, and show that the results obtained compare favorably with previously published results on established benchmarks.

Creator(s): Mihalcea, Rada, 1974-
Creation Date: July 2004
Partner(s):
UNT College of Engineering
Collection(s):
UNT Scholarly Works
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Total Uses: 267
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Creator (Author):
Mihalcea, Rada, 1974-

University of North Texas

Publisher Info:
Place of Publication: [Stroudsburg, Pennsylvania]
Date(s):
  • Creation: July 2004
Description:

Abstract: This paper presents an innovative unsupervised method for automatic sentence extraction using graph-based ranking algorithms. We evaluate the method in the context of a text summarization task, and show that the results obtained compare favorably with previously published results on established benchmarks.

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4 p.

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Subject(s):
Keyword(s): automatic sentence extraction | natural language processing | ranking algorithms
Source: Forty-Second Annual Meeting of the Association for Computational Linguistics, 2004, Barcelona, Spain
Contributor(s):
Partner:
UNT College of Engineering
Collection:
UNT Scholarly Works
Identifier:
  • ARK: ark:/67531/metadc30957
Resource Type: Paper
Format: Text
Rights:
Access: Public