Predicting best match sportsperson for product advertisement

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DC Field	Value	Language
dc.contributor.author	Gopale, Apeksha	-
dc.contributor.author	Shah, Sahil Shakir Hussain [14CO45]	-
dc.contributor.author	Syed, Areeb Iqbal Ahmad [13CO61]	-
dc.contributor.author	Gavandi, Abhay Audumbar [14CO22]	-
dc.contributor.author	Sarguroh, Junaid Jawed [14CO43]	-
dc.date.accessioned	2019-08-01T10:18:10Z	-
dc.date.available	2019-08-01T10:18:10Z	-
dc.date.issued	2019-05	-
dc.identifier.uri	http://www.aiktcdspace.org:8080/jspui/handle/123456789/3202	-
dc.description.abstract	Sports are one of the popular forms of entertainment in today’s world. People do like to express their views on social sites regarding sports, players etc. As we all know that people do watch television, advertisements and show interest in the products endorsed by their favourite sports person. The proposed system is considering the performance or ranking of a sports person and their popularity on social site to decide on the best suitable candidate for particular product endorsement in order to increase the sale of the product. Keywords: Sentimental analysis, Machine Learning, Product Advertisement, Sports, Naive bayes, Prediction.	en_US
dc.language.iso	en	en_US
dc.publisher	AIKTC	en_US
dc.relation.ispartofseries	Pe0580;	-
dc.subject	Project Report - CO	en_US
dc.title	Predicting best match sportsperson for product advertisement	en_US
dc.type	Project Report	en_US
Appears in Collections:	Computer Engineering - Project Reports

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