Sudhanshu S Singh


CVBed: Structuring CVs usingWord Embeddings
Shweta Garg | Sudhanshu S Singh | Abhijit Mishra | Kuntal Dey
Proceedings of the Eighth International Joint Conference on Natural Language Processing (Volume 2: Short Papers)

Automatic analysis of curriculum vitae (CVs) of applicants is of tremendous importance in recruitment scenarios. The semi-structuredness of CVs, however, makes CV processing a challenging task. We propose a solution towards transforming CVs to follow a unified structure, thereby, paving ways for smoother CV analysis. The problem of restructuring is posed as a section relabeling problem, where each section of a given CV gets reassigned to a predefined label. Our relabeling method relies on semantic relatedness computed between section header, content and labels, based on phrase-embeddings learned from a large pool of CVs. We follow different heuristics to measure semantic relatedness. Our best heuristic achieves an F-score of 93.17% on a test dataset with gold-standard labels obtained using manual annotation.