Paper Title
A Cloud Based Recommendation System to Enhance The Employability of Fresh It Gra-Duates

Employability determination is necessary for a fresh graduate since it is significant to meet a number of variables to accomplish the needs of various needs of the skilled candidates in labor market and for the competency of the students who are graduated from any Higher Educational Institution (HEI). Those variables build relation map between various attributes by the representation of a conceptual model. We emphasize here three key components which are Industries, Academies and Students. Those elements are unified for business needs and it will play a vital role in the development of skillful IT professionals. This paper shows ontologically represented recommender system to enhance the present system and balances the demands of the various stakeholders. This is done through a skill analyzer program; that analyzes and updates the scores of students in their profile. It can also recommend an appropriate candidate to the employer based on the industrial needs. The system also helps the students to examine their own skills, potentials to do a self-analysis and the recommendation engine also recommends the methods for improvement based on the job opportunities. It improves the quality of the query results based on the job notifications currently available. This review of domain provides prompt insight about the system and its stakeholders to identify a sub set of suitable resources from a set of options. Our proposed system acts as a tool to implement an academic skill analyzer mechanism in a cloud computing platform. The use of cloud infrastructure helps all stakeholders to keep track of the assessments and its progress if there is a need arising from time to time. Index Terms - Skill Analyzer, Employability, Recommender System, Cloud, Ontology, HEI;