Please use this identifier to cite or link to this item: http://localhost:8080/xmlui/handle/123456789/3202
Title: Predicting best match sportsperson for product advertisement
Authors: Gopale, Apeksha
Shah, Sahil Shakir Hussain [14CO45]
Syed, Areeb Iqbal Ahmad [13CO61]
Gavandi, Abhay Audumbar [14CO22]
Sarguroh, Junaid Jawed [14CO43]
Keywords: Project Report - CO
Issue Date: May-2019
Publisher: AIKTC
Series/Report no.: Pe0580;
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.
URI: http://www.aiktcdspace.org:8080/jspui/handle/123456789/3202
Appears in Collections:Computer Engineering - Project Reports

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