• Dhaval Ganeshbhai Jadav
• Jadav Dhaval
• Patel Jaimini

Products and services are mostly bought by the user by looking at the reviews and ratings. The recommender is an important analysis for traders and buyers which takes multiple criteria in considerations while generating it. Recommender systems use algorithms from data mining to date. Nowadays recommender to provide users with product or service recommendations have been using machine learning algorithms from the field of artificial intelligence too. However, selecting an appropriate machine learning algorithm for a recommender system is difficult because of the number of algorithms. Also, the development of a recommender system using a machine learning algorithm often has problems and open questions that must be evaluated, so where to focus research efforts?. This paper presents a simple and efficient hybrid algorithm that uses a data mining algorithm apriori in a modified way and machine learning algorithm with content-based filtering. In recommender systems to identify opportunities of minimum efforts and yield accurate results is required. The paper concludes that the hybrid algorithm is used in recommender systems because of their relative simplicity, and that requirement and design phases of recommender system development appear to offer opportunities for further research.

"Product Recommendations using Data Mining and Machine Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org), ISSN:2349-5162, Vol.6, Issue 6, page no.702-705, June 2019, Available :http://www.jetir.org/papers/JETIR1907O84.pdf

"Product Recommendations using Data Mining and Machine Learning Algorithm", International Journal of Emerging Technologies and Innovative Research (www.jetir.org | UGC and issn Approved), ISSN:2349-5162, Vol.6, Issue 6, page no. pp702-705, June 2019, Available at : http://www.jetir.org/papers/JETIR1907O84.pdf