Immense growth in communication has paved way for existence of information across the world in wide separated zones. There exists a need for a mechanism to render apt information to the needy from this enormous source of information. This mechanism is of high demand for educational purposes. Knowledge based cloud (Kloud) proposes a solution to combine together the information in different area, which is managed by several organizations. It then organizes them into different sections and hence providing a platform to furnish relevant information to people in search of it. The paper discusses about a method based on Naive Bayes algorithm to classify documents pushed into "Kloud". A variation to this algorithm has been implemented by calculating term weight using "converged weight" method resulting in better accuracy and speed. A comparative study of proposed variance in classification algorithm against the actual algorithm was performed. Further we also implemented two subclassification algorithms namely hierarchical subclassification and subcategorization using document similarity method.
cited By 0; Conference of 2014 International Conference on Data Science and Engineering, ICDSE 2014 ; Conference Date: 26 August 2014 Through 28 August 2014; Conference Code:112595
Shiju Sathyadevan, Sarath, P. R., Athira, U., and Anjana, V., “Improved document classification through enhanced Naive Bayes algorithm”, in Data Science Engineering (ICDSE), 2014 International Conference on, 2014, pp. 100-104.