Affiliation:
1. School of New Media Technology, Hunan Mass Media Vocational and Technical College, Changsha City, Hunan 410100, China
Abstract
Background:
Background: To improve the information efficiency in web text mining, filtration is
utilized.
Methods:
A web content mining technology based on web text mining, augmented information
support (AIS), is proposed for improving the web text mining efficiency. Additionally, the AIS
technology is applied to the Xiangshan science conference website, and AIS4XSSC text mining
system is developed. The developed system is tested for its efficiency, and its main functions are
discussed.
Results:
192 documents are represented by 8352 vectors, and 192×8352 vectors are obtained; the
similarity between 192 vectors is calculated using the cosine of the included angle, 192×192
symmetric matrix is obtained, and 35 categories are formed by hierarchical clustering by using
similarity between texts.
Conclusion:
The results show that the AIS technology can effectively extract information from a
large number of web texts. The proposed system improves information retrieval efficiently and can
provide valuable information to users.
Publisher
Bentham Science Publishers Ltd.
Subject
Electrical and Electronic Engineering,Electronic, Optical and Magnetic Materials