 Investigation and analysis on crowdsourcing for improving enterprise QoSS. Remya and R. Sasikala International Journal of Information Technology and Management, 2021, vol. 20, issue 1/2, 21-48 Abstract: Crowdsourcing is treated as open contest for the crowd of people known as workers. All workers can contribute their suggestions and solutions to the platform. Crowdsourcing can connect a large number of people and they can share their knowledge. The amount of unstructured data is increasing now. This is where crowdsourcing can help bigdata by breaking down the data into mini chunks and have the power of crowd to do the organising task. This helps analytic companies to focus on the core aspect of infrastructure and security. It makes sense of the data and not invests resources in organising the data and this distributed environment can be solved intelligently. Here various crowdsourcing techniques in different aspects related to data pre-processing, performance approaches, security issues and applications are analysed. Out of these approaches the most efficient one in each are characterised. The survey helps to analyse the various issues in crowdsourcing and existing proposed solutions for improving the quality of workers. Keywords: crowdsourcing; bigdata; K-means; data pre-processing; quality control; enterprise. (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:ids:ijitma:v:20:y:2021:i:1/2:p:21-48 Access Statistics for this article More articles in International Journal of Information Technology and Management from Inderscience Enterprises Ltd |
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