Using Artificial Intelligence Approaches to Categorise Lecture Notes
Journal Title: International Journal of Advanced Computer Science & Applications - Year 2018, Vol 9, Issue 8
Abstract
Lecture materials cover a broad variety of documents ranging from e-books, lecture notes, handouts, research papers and lab reports amongst others. Downloaded from the Internet, these documents generally go in the Downloads folder or other folders specified by the students. Over a certain period of time, the folders become so messy that it becomes quite difficult to find our way through them. Sometimes files downloaded from the Internet are saved without the certainty that they will be used or revert to in the future. Documents are scattered all over the computer system, making it very troublesome and time consuming for the user to search for a particular file. Another issue that adds up to the difficulty is the improper naming conventions. Certain files bear names that are totally irrelevant to their contents. Therefore, the user has to open these documents one by one and go through them to know what the files are about. One solution to this problem is a file classifier. In this paper, a file classifier will be used to organise the lecture materials into eight different categories, thus easing the tasks of the students and helping them to organise the files and folders on their workstations. Modules each containing about 25 files were used in this study. Two machine learning techniques were used, namely, decision trees and support vector machines. For most categories, it was found that decision trees outperformed SVM.
Authors and Affiliations
Naushine Bibi Baijoo, Khusboo Bharossa, Somveer Kishnah, Sameerchand Pudaruth
Keywords
Related Articles
- EP ID EP375913
- DOI 10.14569/IJACSA.2018.090842
- Views 93
- Downloads 0
A New Type Method for the Structured Variational Inequalities Problem
In this paper, we present an algorithm for solving the structured variational inequality problem, and prove the global convergence of the new method without carrying out any line search technique, and the global R-conver...
Medical Image De-Noising Schemes Using Different Wavelet Threshold Techniques
In recent years most of researcher’s has done tremendous work in the field of medical image applications such as Magnetic Resonance Imaging (MRI), Ultra Sound, CT scan but still there are many research and experiments in...
Solving Word Tile Puzzle using Bee Colony Algorithm
In this paper, an attempt has been made to solve the word tile puzzle with the help of Bee Colony Algorithm, in order to find maximum number of words by moving a tile up, down, right or left. Bee Colony Algorithm is a ty...
Anonymous Broadcast Messages
The Dining Cryptographer network (or DC-net) is a privacy preserving communication protocol devised by David Chaum for anonymous message publication. A very attractive feature of DC-nets is the strength of its security,...
An Ensemble of Fine-Tuned Heterogeneous Bayesian Classifiers
Bayesian network (BN) classifiers use different structures and different training parameters which leads to diversity in classification decisions. This work empirically shows that building an ensemble of several fine-tun...