Abstract
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.
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Ayyasamy, R.K., Alhashmi, S.M., Eu-Gene, S., Tahayna, B. (2011). Enhancing Concept Based Modeling Approach for Blog Classification. In: Wang, Y., Li, T. (eds) Knowledge Engineering and Management. Advances in Intelligent and Soft Computing, vol 123. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-25661-5_53
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DOI: https://doi.org/10.1007/978-3-642-25661-5_53
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-25660-8
Online ISBN: 978-3-642-25661-5
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