Interest Mining Algorithm Based on Blog Information

Abstract:

Recently, the amount of blogs on the Internet rises sharply. Hence, mining valuable information in blogs possesses realistic significance for improving user experience, network services, etc. This paper proposes a mining algorithm with blog authors' interests based on classification techniques, which introduces an evaluation standard of non-empty intersection. This algorithm can also improve the hit ratio of recommendation service based on blog authors' interests by means of the interest collection from expanding prediction; therefore, it can reach a higher degree of satisfaction. In addition, this paper performs experiments with the data set from Sina Blog and NetEase Blog, whose result illustrates the higher accuracy of our algorithm. Keywords: Blog mining; Interest mining; Classification algorithm; Non-empty intersection.

• Periodical: Applied Mechanics and Materials (Volumes 423-426)
• Pages: 2712-2715
• DOI: https://doi.org/10.4028/www.scientific.net/AMM.423-426.2712
• Online since: September 2013
• Authors: Guo Hua Ou, Chang Jian Xu, Hao Xun Zhan, Yong Qin, Han Huang
• Keywords: Blog Mining, Classification Algorithm, Interest Mining, Non-Empty Intersection

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