An Unstructured Text Analytics Approach for Qualitative Evaluation of Resumes
Vinaya R. Kudatarkar, Manjula M. Ramannavar, Nandini S. Sidnal · 2015
With the growing use of more and more data on networks, big data has become the new trend for productivity, innovation and competition across companies and industries. The proliferation of textual data in businesses is overwhelming. Unstructured or semi-structured textual data is being constantly generated via web logs, emails, documents on the web, blogs, and so on. While the amount of textual data is increasing very rapidly, there is demand for the ability to summarize and analyze in order to make sense of such data for making good business decisions This work reviews how to organize and understand the textual data and presents an unstructured text analytics approach for qualitative evaluation of CV/Resume documents. An effective approach for extracting the resume information from websites and analyzing it thereby making the job easier for finding suitable resumes is presented. The results obtained are a fair measure of qualitative account of a resume document on the parameters of coverage, and comprehensibility and demonstrates the usefulness of the proposed algorithmic approach.