Blog Community Discovery Based on Tag Data Clustering

Authors:
Yu Lu;Hong Lee
Affiliations:
-;-
Venue:
PACIIA '08 Proceedings of the 2008 IEEE Pacific-Asia Workshop on Computational Intelligence and Industrial Application - Volume 02
Year:
2008

Citing 0
Cited 3

A clustering method of bloggers based on social annotations

International Journal of Business Intelligence and Data Mining
Enhancing text clustering model based on truncated singular value decomposition, fuzzy art and cross validation

Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Finding keywords in blogs: Efficient keyword extraction in blog mining via user behaviors

Expert Systems with Applications: An International Journal

Quantified Score

Hi-index	0.00

Visualization

Abstract

Blog is increasingly becoming an important source of information. Blog community is a kind of a group of bloggers with the same interest and common topics on the Internet. To use blog resources effectively, one important way is to identify blog communities and their members in order to refine the blog circle. In this paper, we first define the blog community and the community center, and then construct the blog community discovery algorithm, and next, we collect and analyze the blog tag data from "sina blogsphere". Through the establishment of "blogger- frequency" matrix, we use the clustering method of data mining to implement the discovery of blog communities.