Research on Hotspot Discovery in Internet Public Opinions Based on Improved K-Means
Author
Source
Computational Intelligence and Neuroscience
Issue
Vol. 2013, Issue 2013 (31 Dec. 2013), pp.1-6, 6 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2013-09-10
Country of Publication
Egypt
No. of Pages
6
Main Subjects
Abstract EN
How to discover hotspot in the Internet public opinions effectively is a hot research field for the researchers related which plays a key role for governments and corporations to find useful information from mass data in the Internet.
An improved K-means algorithm for hotspot discovery in internet public opinions is presented based on the analysis of existing defects and calculation principle of original K-means algorithm.
First, some new methods are designed to preprocess website texts, select and express the characteristics of website texts, and define the similarity between two website texts, respectively.
Second, clustering principle and the method of initial classification centers selection are analyzed and improved in order to overcome the limitations of original K-means algorithm.
Finally, the experimental results verify that the improved algorithm can improve the clustering stability and classification accuracy of hotspot discovery in internet public opinions when used in practice.
American Psychological Association (APA)
Wang, Gensheng. 2013. Research on Hotspot Discovery in Internet Public Opinions Based on Improved K-Means. Computational Intelligence and Neuroscience،Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-455751
Modern Language Association (MLA)
Wang, Gensheng. Research on Hotspot Discovery in Internet Public Opinions Based on Improved K-Means. Computational Intelligence and Neuroscience No. 2013 (2013), pp.1-6.
https://search.emarefa.net/detail/BIM-455751
American Medical Association (AMA)
Wang, Gensheng. Research on Hotspot Discovery in Internet Public Opinions Based on Improved K-Means. Computational Intelligence and Neuroscience. 2013. Vol. 2013, no. 2013, pp.1-6.
https://search.emarefa.net/detail/BIM-455751
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-455751