Improved annotation of the blogosphere via autotagging and hierarchical clustering
Proceedings of the 15th international conference on World Wide Web
Eigen-trend: trend analysis in the blogosphere based on singular value decompositions
CIKM '06 Proceedings of the 15th ACM international conference on Information and knowledge management
Expert Systems with Applications: An International Journal
WisColl: Collective wisdom based blog clustering
Information Sciences: an International Journal
Preprocessing of Slovak Blog Articles for Clustering
WI-IAT '10 Proceedings of the 2010 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Volume 03
Formal concept analysis based clustering for blog network visualization
ADMA'10 Proceedings of the 6th international conference on Advanced data mining and applications: Part I
Subject-based extraction of a latent blog community
Information Sciences: an International Journal
On ontology-driven document clustering using core semantic features
Knowledge and Information Systems - Special Issue on "Context-Aware Data Mining (CADM)"
A novel approach for clustering sentiments in Chinese blogs based on graph similarity
Computers & Mathematics with Applications
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Social network captivate huge number of users for learning, advertising, entertaining etc. Blogging is one of the key roles in social environment. Blogs are available in plenty for entertainment, business and educating the blog readers in the World Wide Web. The number of blogs available for technical discussion is numerous and the same can be accessed by the learner for gaining more knowledge from the web. In the current scenario if the blog reader searches the web for a topic, huge number of blogs are retrieved. These blogs are collection of different relevant, irrelevant and non- English language blogs. Blog readers face tedious problem in reading the relevant and useful blogs. In this paper a novel idea is proposed to cluster the blogs according to the document similarity using Hierarchical Agglomerative Clustering. This clustering uses the pre-computed similarity value. This clustering can work to give the users an overview of the contents of a document collection and makes the searching process easier. The experimental result shows that the proposed work yields better results than the other clustering approaches.