• CHANDUPATLA MOUNIKA
• DHUPATI SRIVALLI

With the event of science and technology, a lot of folks particularly young teenagers don't wish to pay a lot of attention to ancient TV programs. Today the challenge of ancient station is a way to attract the audience’s attention, thus on improve the audience rating of tradition TV programs. This paper proposes a recommendation system, which may improve audience rating. This method primarily contains 3 modules. Knowledge gathering module is liable for aggregation audience rating knowledge concerning TV programs on the web. Data processing module is liable for analyzing the audience ration knowledge, and finding attention-grabbing programs that the audiences wish to look at. This program recommendation system is meant to enhance audience rating, and catch the eye of audiences. The system is predicated on large user knowledge and data processing algorithms to research the user’s interests. Compared with ancient recommendation system, it's capable for large knowledge and easier for station to advocate TV programs during which audiences have an interest, as the way to adds vitality to the TV trade.

Computer vision, Classification, Segmentation, Localization, Detection and Recognition, Artificial Intelligence and Machine Learning, Spherical CNN

"A television show Recommendation System supported Big Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 4, page no.204-206, April-2019, Available :http://www.jetir.org/papers/JETIRAZ06041.pdf

"A television show Recommendation System supported Big Data", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 4, page no. pp204-206, April-2019, Available at : http://www.jetir.org/papers/JETIRAZ06041.pdf