A Review on Text Analytics Process with a CV Parser Model

Today, the amount of data generating are very large. Big data are large and complex data sets with an alarming Velocity, Volume and Variety. Depending upon the variations of data, big data constitutes social Data, machine data and transaction based Data. Social data collected from Facebook, Twitter etc. Machine data are RFID chip reading, GPRS etc. Transaction based data includes retail website's data. Around the variations of different types of data major part is text data. Text data is structured data. Deriving of high quality structured data from unstructured text is text analytics. Converting unstructured data into meaningfull data is text analytics process. CV parsing is one of the text analytics technique. It is resume parsing or extraction of CV. CV parser integrate candidate's resume with recruitment work flow and automatically processes incoming CV's. This paper proposes CV parser model using text analytics. The proposed CV parser model extracts entities required in recruitment process in the companies.