UNIQUE PROJECT SELECTION METHOD FOR INSTITUTE

Selecting projects can be a complex task due to the multiple dimensions involved in measuring their impact, especially when there are multiple decision-makers. This paper focuses on a real application of project selection for academic projects, utilizing the opinions of experts through a group decision-making model known as the Topic Selection method. Four types of criteria, including qualitative, quantitative, negative, and positive criteria, are considered for selecting the best project among five options and ranking them accordingly. Additionally, the study utilizes the data from the last five-to-six years to check if any group has already taken up the topic. To achieve this, Support Vector Machine (SVM) Data Mining algorithms are employed. SVMs are chosen for their ability to handle both linear and non-linear data efficiently, making them suitable for this task. By combining the expertise of experts and the power of SVMs, this study aims to provide a robust methodology for project selection in academic settings, considering various dimensions of impact and availability of topics. In conclusion, the project selection process for academic projects requires careful consideration of multiple criteria and the use of advanced techniques such as SVMs for data analysis. By incorporating expert opinions and historical data, the Topic Selection method offers a comprehensive approach to selecting and ranking projects, ensuring that the chosen projects are both impactful and unique within the academic context.