Blogs are user generated content discusses on various topics. For the past 10 years, the social web content is growing in a fast pace and research projects are finding ways to channelize these information using text classification techniques. Existing classification technique follows only boolean (or crisp) logic. This paper extends our previous work with a framework where fuzzy clustering is optimized with fuzzy similarity to perform blog classification. The knowledge base-Wikipedia, a widely accepted by the research community was used for our feature selection and classification. Our experimental result proves that proposed framework significantly improves the precision and recall in classifying blogs. © 2011 Springer-Verlag Berlin Heidelberg.
CITATION STYLE
Ayyasamy, R. K., Alhashmi, S. M., Eu-Gene, S., & Tahayna, B. (2011). Enhancing concept based modeling approach for blog classification. In Advances in Intelligent and Soft Computing (Vol. 123, pp. 409–416). https://doi.org/10.1007/978-3-642-25661-5_53
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