Classification of Questions in Micro-blogging Environment Using Support Vector Machine
Journal Title: International Journal of Research in Computer and Communication Technology - Year 2014, Vol 3, Issue 4
Abstract
Micro-blogging has attracted a growing body of scholarships, because of its popularization. While the use of blogs has spread to a variety of contexts, such as academic research, business and education studies suggest that the prototypical use of blogs as a medium for personal publishing by private non-professionals still dominates over other scenario. Recently it has been well used as a communication tool between a student and the instructor as well as with other students. It can be effectively used for educational purposes. The main objective is to focus on how micro-blogging can be used academically, and on how to analyze micro blogging in the context of learning. It mainly focuses on text categorization for two types of question that has been asked by student’s namely relevant and irrelevant questions. This paper performs the effective classification through Support Vector Machines (SVM), Stop words Removal, Cosine Similarity and Modelling. In addition to the above techniques the results and performance analysis shows using personalization together with question text leads to better categorization accuracy rather than using question text alone.
Authors and Affiliations
Jetlin C. P, Mercy W, Dr. P. S. K Patra
Keywords
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