CISER: Customized Institute Specific Search Engine for Retrieving Research Papers

This paper proposes a methodology of a search engine system for searching research papers customized to our institute students. Most of the courses are associated with course projects where students face difficulties in finding the best research papers associated with the course. So, here we propose a customized mechanism to search the research papers published by the faculties of the institute. The input for the proposed search engine can either be the course name or the topic itself. We give users two options: search by course name and topic. If the course name is given as input, we get the corresponding keywords for the course, and then we implement semantic similarity on the Author Keywords. If the user searches by topic, we perform semantic similarity using the given topic and the Author Keywords of the research papers. We have also created a web interface using Django.