Intelligence Business Model for Skill.jobs with Machine Learning Approaches

dc.contributor.authorTasnim, Zarrin
dc.date.accessioned2022-03-30T06:38:03Z
dc.date.available2022-03-30T06:38:03Z
dc.date.issued2019-12
dc.description.abstractBusiness intelligence and analytics are data management solutions implemented in companies and enterprises to collect historical and present data, while using statistics and software to analyze raw information, and deliver insights for making better future decisions. In the circumstances of today’s world, to survive and established own business need an analytical and find an easiest way or intelligence business model. This study is on “Intelligent business model for skill. Jobs with machine learning approach”. The main objective is to examine the performance of various Machine Learning algorithms in order to perform with the system of skill.jobs. This proposed module integrated with three phase such as, the Clusters similar kind of job search phase (CSK) is a way of knowing the demand is to create a visual graph showing clusters of similar kinds of job searched by the job seekers in the website of skill. jobs, the email notifications send phase (ENS) is responsible to send email notifications to the job seekers when a job circular is posted in the website of skill.jobs, extract the job circular phase (EJC) is the way to extract the job circular post from the career section of each of the company’s website. The result shows the successful clustering of similar job search, email notification send to specific people and extracts the information from the web.
dc.identifier.otherhttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7631
dc.identifier.urihttp://dspace.daffodilvarsity.edu.bd:8080/handle/123456789/7631
dc.language.isoen_US
dc.publisherDaffodil International University
dc.sourceDIU Institutional Repository
dc.subjectIntelligence system
dc.subjectBusiness model
dc.subjectMachine learning
dc.titleIntelligence Business Model for Skill.jobs with Machine Learning Approaches
dc.typeArticle

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