Job Recommendation System based on Machine Learning and Data Mining Techniques using RESTful API and Android IDE

Harsh Jain,Misha Kakkar

2019 9th International Conference on Cloud Computing, Data Science & Engineering (Confluence)(2019)

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摘要
In the current Capitalist world with an abundance of different state-of-the-art industries and fields cropping up, ushering in an influx of jobs for motivated and talented professionals, it is not difficult to identify your field and to persevere to get a job in the respective field but lack of information and awareness render the task difficult. This problem is being tackled by Job Recommendation systems. But not every aspect from the wide spectrum of factors is incorporated in the existing systems. For the "Job Recommendation System - Vitae" machine learning and data mining techniques were applied to a RESTful Web Server application that bridges the gap between the Frontend (Android Application) and the Backend (MongoDB instance) using APIs. The data communicated through APIs is fed into the database and the Recommendation System uses that data to synthesize the results. To make the existing systems even more reliable, here efforts have been done to come up with the idea of a system that uses a wide variety of factors and is not only a one-way recommendation system.
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关键词
Data mining,Machine Learning,Recommendation Systems,Content Based filtering,RESTful API,Android Application,Job Recommendations
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