Using SVM and Stopword removal method in Microblogging Classroom
Journal: International Journal of Science and Research (IJSR) (Vol.4, No. 4)Publication Date: 2015-04-05
Authors : Vidya Dhuttargaon; Amit R. Sarkar;
Page : 981-984
Keywords : Data set; Support VectorMachines SVM; Removal and Cosine Similaritywith Tf-Idf and Okapi techniques;
Abstract
In recent year, Microblogging is a popular technology in social networking applications. All users publish online short text messages with the help of micro blogging which size less than 200 characters. It can be use via web and instant messaging clients etc. It can be an effective tool in the classroom and education community. Microblogging can be categorization for two types such as relevant and irrelevant questions. In relevant questions consistof questions that the teacher wants toaddress in the class. In a question text, empirical results and analysis show that personalizationbetween each other. With the help of question text Microblogging leads to better categorization accuracy. It is also important to utilize the correlation between questions, lecture materials, correlation between questions asked in a lecture. The experimental results likewise demonstrate that the end of stop words which prompts better relationship estimation in the middle of inquiries and arrangement exactness. Then again, fusing understudies' votes on the inquiries that don't enhance classification exactness, despite the fact that a comparable highlight has been indicated to be successful in group inquiry noting situations for evaluating question quality.
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