• Samiksha Pande
• Ashwini Gaikwad

On the Internet, as data available for users is expanding in an exponential rate, the overwhelming size and complexity of the information is also increasing day-by-day. With this rapid development on World Wide Web, we are moving from an environment of data scarcity towards an era of information overload. Now-a-days everyone is having their own intelligent handy devices which is turning them towards the e-commerce sites for their day-to-day chores of purchasing rather than taking out time and visiting number of physical stores. However, the enormous amount of available choices makes the customer indecisive. For the current day, the main challenging task of consumer-oriented e-commerce market is to understand the online customer’s requirements and expectations. Hence this has increased the demand for Recommendation System (RS), which are information filtering system that searches and prioritize information from massive amount of dynamically generated data and recommend more efficiently the item according to user’s interest, preferences and observed behaviour. So, to reduce the impact of large volume data, a Content based and Rating based Recommendation system is proposed. This system aims at reducing the shortcoming of Collaborative and Content based methods individually, by parallelly using both methods in one System.

E-commerce, Recommendation system, Content based, Rating based, Collaborative Filtering.

"Content Based and Rating Based Book Recommendation System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 5, page no.410-417, May-2019, Available :http://www.jetir.org/papers/JETIR1905773.pdf

"Content Based and Rating Based Book Recommendation System", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 5, page no. pp410-417, May-2019, Available at : http://www.jetir.org/papers/JETIR1905773.pdf