Review of job recommender system using big data analytics

The war on talent, supply demand issues, shifting growth paradigms across different sectors form part of the ecosystem in which we live and operate, which is constantly evolving, adaptating and increasing the use of advanced technologies to solve problems across the Talent supply chain domain. Innovations and value added extensions and services are required at a corporate and individual level. At present, we have number of online services which impact our lives in different ways. E-recruitment is one of the known and popular online service for the job seekers as well as for the employers. Past proposed job recommender systems worked with small and structured data sets. But today we have large amount of heterogeneous and unstructured data in comparison to structured data which is growing at tremendous speed. Past proposed techniques of job recommender system does not work adequately on Big Data. Hence, we need more advanced techniques for handling Big data. In this paper, we explored recent work on job recommender system and the research gap between current abilities and new requirements were identified. We proposes a new job recommendation framework which handle Big data effectively.