Resume Classifier and Summarizer

The tool developed by us is for categorizing and summarizing the resumes. The text was cleaned by transformation to a better encoding scheme, removal of punctuation marks, stop words, and everything was reduced to lower case to avoid redundancy. Following the rigorous cleaning, the text was passed to our model for classification, which accurately predicts the category of resume. The overall output of our model would be the class of the input resume along with a summarized version of the resume for the process of classification, different models were tried out including Logistic Regression, multinomial Naive Bayes, Support Vector Machines. After repeated cleaning and training, our model was seen to perform well with an overall accuracy of 70% using Support Vector Classifier.