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Intelligent radio listenership monitoring platform

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dc.contributor.author Rodirgo, Suhash
dc.date.accessioned 2023-01-13T08:21:27Z
dc.date.available 2023-01-13T08:21:27Z
dc.date.issued 2022
dc.identifier.citation Rodirgo, Suhash (2022) Intelligent radio listenership monitoring platform. MSc. Dissertation, Informatics Institute of Technology en_US
dc.identifier.issn 20200968
dc.identifier.uri http://dlib.iit.ac.lk/xmlui/handle/123456789/1416
dc.description.abstract "The ability of the media to successfully shape public opinion is undeniable. Radio has always been widely considered as a part of the mainstream media in Sri Lanka. It has been recommended to have a complete radio listenership monitoring platform to monitor the listenership of each channel in light of the intense competition among the various radio channels in Sri Lanka. Currently, a diary-based system is used to monitor the radio listenership in Sri Lanka. However, the time has come to develop an advanced intelligent radio listenership monitoring platform to cater to this requirement which will enable better comprehension of the requirements and preferences of the general public. With the help of this research, machine learning technologies and other neural network technologies will be combined to create an intelligent radio listenership monitoring platform that is both reliable and accurate. This research will present a fool-proof approach of monitoring the radio listenership, which will resolve many of the practical challenges that have been a part of the current diary-based system. Radio channel heads advertisers and marketing businesses will find this important information supplied by the solution to be helpful in understanding the public interest and positioning their advertisements on appropriate segments. " en_US
dc.language.iso en en_US
dc.subject Big data en_US
dc.subject Machine learning en_US
dc.subject Sound recognition en_US
dc.title Intelligent radio listenership monitoring platform en_US
dc.type Thesis en_US


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