A Multi Layer Perceptron Classifier for Content-based Recommender System
K.R.Sekar1, Makkena Sai Kumar2, Mogadampalli Jayanth3, N.Sivaramakrishan4, G.Sathiamoorthy5
1K.R.Sekar , Department of Computing, SASTRA Deemed University, Tirumalaisamudram Thanjavur (Tamil Nadu), India.
2Makkena Sai Kumar, Department of Computing, SASTRA Deemed University, Tirumalaisamudram Thanjavur (Tamil Nadu), India.
3Mogadampalli Jayanth, Department of Computing, SASTRA Deemed University, Tirumalaisamudram Thanjavur (Tamil Nadu), India.
4N.Sivaramakrishan, Department of Computing, SASTRA Deemed University, Tirumalaisamudram Thanjavur (Tamil Nadu), India.
5G.Sathiamoorthy, Department of Humanities and Science, SASTRA Deemed University, Tirumalaisamudram Thanjavur (Tamil Nadu), India.
Manuscript received on 07 April 2019 | Revised Manuscript received on 20 April 2019 | Manuscript published on 30 April 2019 | PP: 767-771 | Volume-8 Issue-6, April 2019 | Retrieval Number: F3665048619/19©BEIESP
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Abstract: For the past one and half year decades, recommended system is playing a vital role and providing the outline and peripheral information to the mobile customers. The objective of the work is to recommend good quality mobiles for the requirement of the customers with all required amenities. Multilayer perceptron neural network classifier is the methodology deployed and employed for the recommendations. The result outcome will always be very precise and has got a high precision of accuracy because of the above said methodology. Reliability and the accuracy are the prominent factors to the non-functional activity and the customers to buy the trusted mobiles from the shopping cart. Ordinal values will taken into account for the evaluation of ten top mobiles. The real characterization can be gauged through the recommendation given by the customers in the respective portals. Customers’ sentiments and the values of their comments are the features used to gauge the commodity values. Overall in the research work recommendations are classified into supervised leanings. Non minor can easily get the most favorite mobile with existing money affordable by them to buy the mobile commodity.
Keyword: Multilayer Perceptron, Reliability, Accuracy, Recommender System and Sentiment analysis.
Scope of the Article: Web-Based Learning: Innovation and Challenges