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Autonomous text summarization using collective intelligence based on nature-inspired algorithm
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Publication Year
2018-01-01
Journal
Lecture Notes in Electrical Engineering
Publisher
Springer Verlag
Citation
Lecture Notes in Electrical Engineering, Vol.425, pp.455-464
Keyword
Ant colony systemAutomated text summarizationNatural language processing
Mesh Keyword
Ant colony algorithmsAnt colony systemsCollective intelligencesContinuous flowsHardware technologyNature inspired algorithmsTest summarizationText summarization
All Science Classification Codes (ASJC)
Industrial and Manufacturing Engineering
Abstract
Thousands of years ago written language was introduced as a way of enhancing and facilitating communication. Fast forward to the twenty first century much has changed, especially the flow of data incrementing at fast rate and we should use the power of algorithms and hardware technology to understand text more clearly. With the Information age rising we are being cluttered with humongous data each day with no sign of it slowing. Humans have been trying to create ways on how to handle this continuous flow of text, image and video. And one of the categories of subjects regarding text is text summarization, given a document coming up with a reasonable summarized version of the original document. People have tried different aspects of summarizing to get a shorter yet an informative definition of document. This paper tries to utilize using nature inspired algorithms to implement an auto summarizer of text using pseudo-selected features. The main objective of this research is to use of cooperative nature-inspired algorithm specifically ant colony algorithm in text mining problems, in our case, text summarization. And throughout the paper we will try to show how this system can be achieved as well as show the performance and effectiveness of the measurement. We have used the standard data used to test summarization techniques, DUC data and at last comparing it to two algorithms for further analysis.
Language
eng
URI
https://aurora.ajou.ac.kr/handle/2018.oak/36339
https://www.scopus.com/inward/record.uri?partnerID=HzOxMe3b&scp=85022175933&origin=inward
DOI
https://doi.org/2-s2.0-85022175933
Journal URL
http://www.springer.com/series/7818
Type
Conference
Funding
This research was supported by the Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education [NRF-2016R1D1A1B03933875].
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Sohn, Kyung-Ah Image
Sohn, Kyung-Ah손경아
Department of Software and Computer Engineering
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