implementation and evaluation of trust based recommendation system for next generation agriculture

Abstract

Precise recommendations and proper guidance are essential for young farmers to resolve problems in developing agriculture.In reality, the farming sector has limited knowledge to share and agricultural experts are less in number. The online platforms for agriculture sector available at present simply provide regular solutions but not customized solutions as per the specific requirement. Hence, it is highly difficult to solve the farmers issues. The research work proposes to develop a recommender system by analyzing the numerous reviews given by the various users. The data that is used for processing information depends upon the type of recommender systems. These recommender systems play a major role in providing recommendations about agriculture-related reviews such as crop yielding, water management, soil analysis, etc. There are several issues in agriculture recommender systems such as lack of accuracy in the data of agriculture. Through the present study, a hybrid online farming framework is proposed to address the major issues affecting the agricultural production in India.It makes use of frequently asked questions in the field, gets recommendations and solutions from experts in agricultural technology. The framework works in such a way that the users get suggestions as per their requirement. The system is designed to predict best suitable recommendations for mixed cropping, crop rotation, irrigation, seed treatment ,fertilizer and suggestions on pesticides etc. newline newlineThrough this framework, the queries submitted by farmer are processed by using modified stemming algorithm and distinct semantic keywords are obtained relative to the submitted query. The keywords are then sent to database or to agricultural technology personnel or expert for customized recommendations to the farmer. The recommendations are then analyzed and ranked based on their effective usage and reliability score. newline