Using the Essence of Texts to Improve Document Classification

Description:

This article discusses using the essence of texts to improve document classification.

Creator(s):
Creation Date: September 2005
Partner(s):
UNT College of Engineering
Collection(s):
UNT Scholarly Works
Usage:
Total Uses: 81
Past 30 days: 2
Yesterday: 0
Creator (Author):
Mihalcea, Rada, 1974-

University of North Texas

Creator (Author):
Hassan, Samer

University of North Texas

Date(s):
  • Creation: September 2005
Description:

This article discusses using the essence of texts to improve document classification.

Degree:
Note:

Abstract: This paper explores the possible benefits of the interaction between automatic extractive summarization and text classification. Through experiments performed on standard test collections, we show that techniques for extractive summarization can be effectively combined with classification methods, resulting in improved performance in a text categorization task. Moreover, comparative results suggest that the synergy between text summarization and text classification can be regarded as a new application-oriented evaluation testbed for automatic summarization.

Physical Description:

8 p.

Language(s):
Subject(s):
Keyword(s): automatic extractive summarizations | text classifications
Source: Conference on Recent Advances in Natural Language Processing (RANLP), 2005, Borovetz, Bulgaria
Contributor(s):
Partner:
UNT College of Engineering
Collection:
UNT Scholarly Works
Identifier:
  • ARK: ark:/67531/metadc30978
Resource Type: Paper
Format: Text
Rights:
Access: Public