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Authors: Hua Li ; Daniel J. T. Powell ; Mark Clark ; Tifani O'Brien and Rafael Alonso

Affiliation: Leidos Inc., United States

ISBN: 978-989-758-158-8

Keyword(s): User Modeling, Expertise Modeling, Resume, Profile, Skill.

Related Ontology Subjects/Areas/Topics: Artificial Intelligence ; Enterprise Information Systems ; Intelligent Information Systems ; Knowledge Management and Information Sharing ; Knowledge-Based Systems ; Organizational Memories ; Symbolic Systems ; Tools and Technology for Knowledge Management

Abstract: Job applicants describe their skills and expertise in resumes and curriculum vitaes (CVs). These biographic data are often evaluated by human resource personnel or a search committee. This manual approach works well when the number of resumes is small. However, in this information age, the volume of available resumes can be overwhelming and there is a need for automatic evaluation of applicant skills and expertise. In this paper, we describe a user modeling algorithm to quantitatively identify skills and expertise from biographic data. This algorithm is called REMA (Resume Expertise Modeling Algorithm). REMA takes data from a resume document as input and produces an expertise model. The expertise model details the expertise topics for which the resume owner has claimed competency. Each topic carries a weight indicating the level of competency. There are two key insights for this algorithm. First, one’s expertise is the cumulative result of the various “learning events” in one’s career . These learning events are mentioned in various sections of the resume, such as earning a degree, writing a paper, or getting a patent. Second, one’s knowledge and skills can become outdated or forgotten over time if not reinforced by learning. We have developed a prototype resume evaluation system based on REMA and are in the process of evaluating REMA’s performance. (More)

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Paper citation in several formats:
Li, H.; J. T. Powell, D.; Clark, M.; O'Brien, T. and Alonso, R. (2015). User Modeling of Skills and Expertise from Resumes.In Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS, (IC3K 2015) ISBN 978-989-758-158-8, pages 229-233. DOI: 10.5220/0005622202290233

@conference{kmis15,
author={Hua Li. and Daniel J. T. Powell. and Mark Clark. and Tifani O'Brien. and Rafael Alonso.},
title={User Modeling of Skills and Expertise from Resumes},
booktitle={Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS, (IC3K 2015)},
year={2015},
pages={229-233},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005622202290233},
isbn={978-989-758-158-8},
}

TY - CONF

JO - Proceedings of the 7th International Joint Conference on Knowledge Discovery, Knowledge Engineering and Knowledge Management - Volume 3: KMIS, (IC3K 2015)
TI - User Modeling of Skills and Expertise from Resumes
SN - 978-989-758-158-8
AU - Li, H.
AU - J. T. Powell, D.
AU - Clark, M.
AU - O'Brien, T.
AU - Alonso, R.
PY - 2015
SP - 229
EP - 233
DO - 10.5220/0005622202290233

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