Agriculture is the main sector of employment in India. Yet, it contributes only 13.7% to the total GDP of India. One of the major causes for the continuing downfall in agricultural trends is cultivation of crops that are not suitable with the environmental factors like soil and weather conditions. One way to solve this problem is to use the Recommendation System. It is the information filtering system forecasting the items that may be additional interest for user within a big set of items on the basis of user’s interests. This system uses the Collaborative filtering, which offer some recommendations to users on the basis of matches in behavioral and functional patterns of users and also shows similar fondness and behavioral patterns with those users. It also seeks to predict the suitability of an item for a given set of conditions. Such a recommendation system can provide suggestions for a crop that can be cultivated based on soil and weather conditions. The research focus on to build a recommendation system that can collect raw data for environmental factors like soil, weather parameters from experienced farmers, agricultural researchers and other stakeholders. The collected data then will be maintained whether this data is processed. Statistic data analysis and predictive modeling are applied in order to predict a suitable crop accordingly.

Recommendation System, Agriculture, Collaborative Filtering, Predictive Modeling

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