Abstract
Context-aware systems are getting rapid popularity towards enabling a pervasive computing environment over hand-held mobile devices, wearable devices, and Tablets. These systems deliver services tailored to the specific needs and user’s context. The context-aware system services can utilize information about the user’s context to adapt services based on the user’s location. The prime aim of this research paper is to investigate and analyse the critical issues and challenges while delivering the job information to the job seekers when they migrate from one place to another in search of jobs. In addition, the research also tries to investigate the challenges faced by employers/ job providers when they search and recruit the right person for the right jobs. In this paper the issues and challenges investigated and analysed were timeliness of information dissemination, opportunity missing, fake/genuine information, anywhere, anytime accessibility over small handheld devices. After rigorous analysis of the investigated issues and challenges in the existing state of art employment/job information dissemination systems, a real-time context-aware employment information delivery system framework for the pervasive environment is proposed. The research parameters considered are Preference of Job seekers, Location of Jobs, Context, Qualification, CGPA, Experience, everywhere access at any time, and Identity. The paper used both the quantitative and qualitative approaches for proposing a research-based applied solution. Survey of job seekers, Interview of recruiters, and technical observation of the researcher are used for collecting the relevant facts to check the researchability of the issues and challenges. Protégé version 4.3 is used for modelling, Edraw-Max for designing the framework, Google Form for Survey, and Justin mind tool for Prototype design and testing. The framework and its Prototype was examined using a user acceptance test. The acceptance test indicated that 84.6% of target stakeholders accepted the proposed system framework as a new knowledge solution for the aforementioned issues and challenges in the employment sectors
Highlights
In the current state of the art, information regarding vacancies, posts, or jobs in Ethiopia both by government and non-government organizations are disseminated/communicated either via the organization website or via general job posting websites and notice boards of organizations/private facilitators
This module of the system framework performs its tasks based on two cases- 1) one is during Event Notifier modules notifies the occurrence of a special event, 2) Preference Discovery module submits context information to be dispatched to a user based on his/her profile history
This research proposes a framework for context-aware real-time job information delivery in a pervasive environment
Summary
In the current state of the art, information regarding vacancies, posts, or jobs in Ethiopia both by government and non-government organizations are disseminated/communicated either via the organization website or via general job posting websites and notice boards of organizations/private facilitators. 6) The existing system practices are time-consuming, cost consuming, tiresome, boring, and in a bureaucratic structured manner These potential issues and challenges inspired this research to design a “Reverse Search Framework” for context-aware job searching with intelligent content/ job preferences. Ethiopia has an acute shortage of such kinds of systems that can provide a localized guideline to develop such systems to facilitate the real-time job search flow from " job providers" to "Job seekers" i.e. organization website or general job posting websites or notice boards of the organizations/private facilitators to the Job Seekers/Aspirants in real-time fashion using job seekers Context-aware Profile (i.e. Qualification, CGPA, Experience, anywhere-anytime job information, identity, and Preference) and their Context-aware Location (i.e. Cell ID, RSSI, IMEI, and GSM), etc. This can help them determine and find suitable jobs with their requirement specifications and specialization
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