AI Resume Analyzer Using Natural Language Processing and Data Mining

AI Resume Analyzer Using Natural Language Processing and Data Mining

Project Guide: Prof. Jayashri Mankar

1.Abhishek Chauhan, 2.Aniket Gophane, 3.Aditya Karle, 4.Taslimarif Makandar

BE Students

Department of Computer Engineering

Genba Sopanrao Moze College of Engineering Balewadi, Pune-411045, Maharashtra, India

Abstract

            Imbalance data conversion into structured data is the very tedious task in data mining techniques, various techniques have been already introduced to extract the data from large text and extract the features using various feature extraction techniques, some machine learning algorithms have been already introduced by various researchers for classification and display the results on heterogeneous data. This work suggests a method of eliminating or resuming important information in a curriculum vitae from the semi-structured text format, and rating it according to the preference and requirements of the client. The whole process was divided into three basic sections to achieve the desired goal. The first section consists of segmenting the whole Summary according to the content of each part, the second section consists of extracting data in a standardized form from unstructured data and the final section consists of analyzing structured data using NLP and Machine learning algorithms. The Stanford NLP rule extraction algorithm ha used to extract the various rules from raw data and select some important feature for classification as well as optimization. Experimental analysis shows the effectiveness of proposed system with classification accuracy.

Keywords : Resume parsing, Data Mining, Machine learning, NLP