Abstract
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.
Highlights
With recent advancements in technology, human reliance on the internet has increased greatly.Information is mostly available and shared via the internet using sources, such as websites, social media and web portals
The context-aware information is stored in the knowledge base built using Linked Open Data principles
These values are computed by comparison with the gold standard data-set manually verified by Human Resource (HR) experts
Summary
Information is mostly available and shared via the internet using sources, such as websites, social media and web portals. This advancement in internet technology has had an impact on recruiting potential employees for an organization.Various e-recruitment systems have flourished, such as (https://www..com), Monster (https://www.monster.com/), Person force (https://www.personforce.com/), and Angel.co (https://angel.co/). E-recruitment facilitates both employers and users in terms of finding relevant jobs efficiently. Existing e-recruitment systems use keywords or faceted searches //www.personforce.com/; https://angel.co/) to provide better search results to both organization and users. Domain Independent Knowledge Base Population from Structured and Unstructured Data Sources.
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
