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Article

A New Approach to Information Extraction in User-Centric E-Recruitment Systems

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SEECS, National University of Sciences and Technology, Islamabad 44000, Pakistan
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Biome Analytics, Islamabad 44000, Pakistan
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College of Technological Innovation, Zayed University, Abu Dhabi 144534, UAE
*
Author to whom correspondence should be addressed.
Appl. Sci. 2019, 9(14), 2852; https://doi.org/10.3390/app9142852
Received: 26 June 2019 / Revised: 11 July 2019 / Accepted: 15 July 2019 / Published: 17 July 2019
(This article belongs to the Section Computing and Artificial Intelligence)
In modern society, people are heavily reliant on information available online through various channels, such as websites, social media, and web portals. Examples include searching for product prices, news, weather, and jobs. This paper focuses on an area of information extraction in e-recruitment, or job searching, which is increasingly used by a large population of users in across the world. Given the enormous volume of information related to job descriptions and users’ profiles, it is complicated to appropriately match a user’s profile with a job description, and vice versa. Existing information extraction techniques are unable to extract contextual entities. Thus, they fall short of extracting domain-specific information entities and consequently affect the matching of the user profile with the job description. The work presented in this paper aims to extract entities from job descriptions using a domain-specific dictionary. The extracted information entities are enriched with knowledge using Linked Open Data. Furthermore, job context information is expanded using a job description domain ontology based on the contextual and knowledge information. The proposed approach appropriately matches users’ profiles/queries and job descriptions. The proposed approach is tested using various experiments on data from real life jobs’ portals. The results show that the proposed approach enriches extracted data from job descriptions, and can help users to find more relevant jobs. View Full-Text
Keywords: semantic web; information retrieval; information extraction; e-recruitment semantic web; information retrieval; information extraction; e-recruitment
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MDPI and ACS Style

Ahmed Awan, M.N.; Khan, S.; Latif, K.; Khattak, A.M. A New Approach to Information Extraction in User-Centric E-Recruitment Systems. Appl. Sci. 2019, 9, 2852. https://doi.org/10.3390/app9142852

AMA Style

Ahmed Awan MN, Khan S, Latif K, Khattak AM. A New Approach to Information Extraction in User-Centric E-Recruitment Systems. Applied Sciences. 2019; 9(14):2852. https://doi.org/10.3390/app9142852

Chicago/Turabian Style

Ahmed Awan, Malik N., Sharifullah Khan, Khalid Latif, and Asad M. Khattak. 2019. "A New Approach to Information Extraction in User-Centric E-Recruitment Systems" Applied Sciences 9, no. 14: 2852. https://doi.org/10.3390/app9142852

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