Generating An Optimal Interview Question Plan Using A Knowledge Graph And Integer Linear Programming

Soham Datta, Prabir Mallick, Sangameshwar Patil, Indrajit Bhattacharya, Girish Palshikar


Abstract
Given the diversity of the candidates and complexity of job requirements, and since interviewing is an inherently subjective process, it is an important task to ensure consistent, uniform, efficient and objective interviews that result in high quality recruitment. We propose an interview assistant system to automatically, and in an objective manner, select an optimal set of technical questions (from question banks) personalized for a candidate. This set can help a human interviewer to plan for an upcoming interview of that candidate. We formalize the problem of selecting a set of questions as an integer linear programming problem and use standard solvers to get a solution. We use knowledge graph as background knowledge in this formulation, and derive our objective functions and constraints from it. We use candidate’s resume to personalize the selection of questions. We propose an intrinsic evaluation to compare a set of suggested questions with actually asked questions. We also use expert interviewers to comparatively evaluate our approach with a set of reasonable baselines.
Anthology ID:
2021.naacl-main.160
Volume:
Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies
Month:
June
Year:
2021
Address:
Online
Editors:
Kristina Toutanova, Anna Rumshisky, Luke Zettlemoyer, Dilek Hakkani-Tur, Iz Beltagy, Steven Bethard, Ryan Cotterell, Tanmoy Chakraborty, Yichao Zhou
Venue:
NAACL
SIG:
Publisher:
Association for Computational Linguistics
Note:
Pages:
1996–2005
Language:
URL:
https://aclanthology.org/2021.naacl-main.160
DOI:
10.18653/v1/2021.naacl-main.160
Bibkey:
Cite (ACL):
Soham Datta, Prabir Mallick, Sangameshwar Patil, Indrajit Bhattacharya, and Girish Palshikar. 2021. Generating An Optimal Interview Question Plan Using A Knowledge Graph And Integer Linear Programming. In Proceedings of the 2021 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, pages 1996–2005, Online. Association for Computational Linguistics.
Cite (Informal):
Generating An Optimal Interview Question Plan Using A Knowledge Graph And Integer Linear Programming (Datta et al., NAACL 2021)
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PDF:
https://aclanthology.org/2021.naacl-main.160.pdf
Video:
 https://aclanthology.org/2021.naacl-main.160.mp4