DOIONLINE 
DOIONLINE Publish In |
International Journal of Advance Computational Engineering and Networking (IJACEN)-IJACEN |
 Journal Home Volume Issue |
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Issue |
Volume-3, Issue-8 ( Aug, 2015 ) | |||||||||
Paper Title |
Knn Based Twitter Newscaster | |||||||||
Author Name |
Prasad j. Koyande, kavita P. Shirsat | |||||||||
Affilition |
Computer Engineering, Mumbai University, Vidyalankar Institute of Technology, VIT Mumbai, India | |||||||||
Pages |
85-88 | |||||||||
Abstract |
With the popularity of Social Networks, mostly news providers used to share their news in various social networking sites and web blogs. In India, many news groups share their news on Twitter micro blogging service provider. These data carries valuable information relevant to social research areas. Thus, the idea is to categorize the news into different groups so the news groups in India are identified. News groups are selected on their popularity to extract the short messages from Twitter Micro Blog. Short message extracted from Twitter was classified into 12 major groups. Machine learning techniques were used to train the data. In order to create the instances words from each short message were consider and bag-of-words approach was used to create feature vector. The data was trained using KNN (K – Nearest Neighbor) machine learning techniques. The KNN is a typical learning algorithm based on analogy, so each category has a certain amount of the training samples which helps representatives guarantee the accuracy of classification. Large amount of feature will be collected for current research.The performance will speak the efficacious of the system. Keywords- KNN, Web Mining, Text Classification | |||||||||
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