Abstract:
The objective ofthis project is to develop a recommender system with help ofmachine
learning algorithms. The recommender system will be able to recommend jobs itself
by comparing tags ofthe user present in the dataset. This report explores techniques
used or involved in designing recommender system. Different stages involving data
pre-processing stage, data cleaning and database design will be studied and discussed.
Finally the end product will be the obviously the recommender system which will
recommend jobs which is basically the main functionality and we students will try to
integrate it with user friendly interface or will develop a website which will be our
secondary task.
This project uses the Machine learning technique (binary classification) to develop the
system. The main advantage of using this technique is that it provides the result by
simply calculating its probability of occurrence.
The system first checks the user field of interest (from the dump dataset of stack
overflow) that in which field he is answering the questions most in stack overflow then
the system will automatically recommend the job that are present in our dataset and
displays to the user
