This paper proposes an innovative approach in managing project related documents, project domain analysis and recommendation of open areas from current project document pool. Using Keyterm Extraction technique, documents are tagged under appropriate categories and sub-categories for better management of project documents. Hence this tagged document serves as reference for the students who are planning to take up new projects. The system generates various reports for statistical analysis of projects carried out in each research domain. These statistics benefits users to get an overview of the trends of project works done over the past few years. There are also reports illustrating number of open areas over respective academic years. The open areas are identified and listed for the students. This novel approach would help the students who are seeking new project. Our system helps the students, faculty and other academicians to get involved in ongoing projects and also to obtain ideas in their respective research domain. We have modified the stemming method in basic Keyterm Extraction algorithm (KEA) by adding Porter stemmer rather than Lovins stemming method and our experimental results confirms that our modified Keyterm Extraction method outperforms the KEA method while tagging English documents.
Thushara M. G., SA, S., and S, S., “KEA based Document Tagging for Project Recommendation and Analysis”, ICACNI 2017 : 5th International Conference on Advanced Computing, Networking, and Informatics, At National Institute of Technology. Goa, 2017.