Create Special Domain News Collections through Summarization and Classification

Authors

  • Zhi Teng,

    Student Member, Corresponding author
    1. Graduate School of Advanced Technology and Science, The University of Tokushima, 2-1 Minamijosanjima, Tokushima 770-8506, Japan
    • Graduate School of Advanced Technology and Science, The University of Tokushima, 2-1 Minamijosanjima, Tokushima 770-8506, Japan
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  • Ye Liu,

    Student Member
    1. Graduate School of Advanced Technology and Science, The University of Tokushima, 2-1 Minamijosanjima, Tokushima 770-8506, Japan
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  • Fuji Ren

    Member
    1. Institute of Technology and Science, The University of Tokushima, 2-1 Minamijosanjima, Tokushima 770-8506, Japan
    2. School of Information Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China
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Abstract

In this paper, we present a novel technique to create a special domain news collection system from really simple syndication (RSS) news sites through summarization and classification. The main aim of this research is to build a self-sufficient news collection system in disaster domain. In this news collection system, we used new strategies and algorithms to mine news from RSS sites, recognized and collected disaster news using automatic summarization and classification. The most striking dissimilarity between our study and previous work is that we use a novel summary approach to improve the classification performance. This paper discusses the effect of summarization and classification model on system performance. Results show that our method yields a better performance in this field. Copyright © 2010 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.

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