A New Approach to Automated Summarization based on Fuzzy Clustering and Particle Swarm Optimization

Automated Summarization of the text is now become an important aspect as it makes the meaning of documents easy to understand and easy to read. Automated summarization is the process of decreasing a text document with a computer system to be able to develop a synopsis that retains the main points as...

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Bibliographic Details
Published in:International journal of computer applications 2016-01, Vol.148 (1), p.12-15
Main Authors: Yadav, Rahul Kumar, Singh, Sugandha
Format: Article
Language:English
Subjects:
Algorithms
Automation
Clustering
Fuzzy
Swarm intelligence
Texts
Online Access:Get full text
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Summary:Automated Summarization of the text is now become an important aspect as it makes the meaning of documents easy to understand and easy to read. Automated summarization is the process of decreasing a text document with a computer system to be able to develop a synopsis that retains the main points associated with document this is certainly initial. Once the irritating dilemma of information overload is continuing to grow, and as the total amount of data has increased, so has fascination with automated summarization. A typical example of the application of summarization technology such as for example Bing and Document summarization is another. There are number of clustering algorithms which have been used in the past as clustering plays significant role in summarizing of the documents. In this paper, we discussed about the existing clustering algorithms. We also proposed a hybridized algorithm based on the combination of fuzzy C-Means and Particle Swarm Optimization. In the last, we compared our proposed algorithm results with the existing clustering algorithms.
ISSN:0975-8887
0975-8887
DOI:10.5120/ijca2016910972