Recommendation of Marketplace using Filter-based Model for Farmers

Agriculture and related industries are vital for rural employment and income, contributing significantly to the country's economy. However, agricultural productivity in India lags behind other countries, especially in terms of yield per unit of land. This low productivity, coupled with financial challenges, has led to a concerning trend of farmer suicides, particularly among small-scale farmers. Increasing agricultural revenue and production requires action for dealing with these problems. This paper proposes a recommendation system for farmers to choose the best marketplace for their crops, based on analyzing historical data from various Agricultural Produce Market Committee (APMC) datasets. The recommendation model of content-based and collaborative filtering techniques and is trained on data from APMCs in Amravati District, Maharashtra, India. The model demonstrates improved performance, achieving higher recall rates at both top-5 and top-10 recommendations.