Development of an intelligent academic supporting tool - Liew,, Hui Chang. (Universiti Malaysia Sarawak, UNIMAS, 2009)
Academic supporting tool is defi ned as an educational development services which is developed as a guide to universi ties and colleges in order to support and help in academic progress. In this th esis, two academic supporting tools; e.g., an electronic notification system, and an Evolving Tree (ETree) based automated documents clustering system are deve loped, and evaluated. The electronic notification system with S hort Message Service (SMS) technology is developed to facilitate the communication among lecturers and students. It can be viewed as a mobile, efficient and environment-friendl y communication platform among lecturers and students. It allows latest news, gene ral notices, instant cla ss cancellation alerts and etc. to be deliv ered to students in stantly, through SMS. The electronic notification system is developed using Visual Basic language. Practicality of the developed system is further evaluated with the help of a lecturer in UNIMAS. Positive results are obtained. The ETree based automated documents clustering system is developed to allow conference papers to be clustered, organized and visualized based on their abstract similarit y. Classification of conference papers is always a tedious, time-consuming and e xpensive task, to be carried out by experience academicians. The developed sy stem is a decision supporting tool for conference organizers and technical committees. It eases the task of classification of conference papers. With re gards to the study of neural network, ETree is proposed as an improvement of Self Organizing Map (SOM). As compared with conventional SOM, ETree does not require map size to be predetermined. From literature, the use of SOM in document clustering, organizati on and visualization problems has been widely reported. However, from literature review, the main application of ETree centered at image processing, and no re port on the use of ETree in document clustering, organization and visu alization problems have be en found. To some extent, this piece of work can be viewed as an earlier investigation on the use ETree for document classification problems. The ETree based automated documents clustering system is evaluated with in formation from Engineering Conference (ENCON) 2008. Correctness of the clustering result is further evaluated with the help of a Technical Committee from ENCO N 2008. Experiments show that it is a potential system, and positive results are obtained.