Litcius/Paper detail

AgriResponse: A Real-Time Agricultural Query-Response Generation System for Assisting Nationwide Farmers

Samarth Godara, Jatin Bedi, Rajender Parsad, Deepak Singh, Ram Swaroop Bana, Sudeep Marwaha

2023IEEE Access11 citationsDOIOpen Access PDF

Abstract

Advancements in information sciences can play a vital role in strengthening the nation’s sustainable agriculture goals. In this direction, we propose a framework for a text-based query-response generation system to cope with the demand for timely help to the nationwide Indian farmers. One of the major challenges in designing such systems is constructing a knowledge base that can answer plant-protection-related questions from a diverse population of farmers. To tackle this problem, the past eight years’ call-log records from the countrywide farmers’ helpline network are collected and processed to construct the required knowledge base. Additionally, three response-retrieval models with approximate matching and spatial-based searching functionality are developed to administer the user input questions and extract relevant answers from the base. To validate the performance of the proposed framework, a diversified question bank consisting of 755 queries covering 151 crops in India is compiled. Three metrics (Accuracy Percentage, Crop-weighted Performance Score, and Average Response-retrieval time) are considered for the models’ assessment. Experimental results show that AgriResponse is a practical framework in real-world applications, with the different retrieval models useful for different scenarios.

Topics & Concepts

Computer scienceMatching (statistics)HelplineConstruct (python library)AgricultureKnowledge basePopulationInformation retrievalData scienceWorld Wide WebGeographyStatisticsProgramming languageArchaeologySociologyMedicineMathematicsEmergency medicineDemographyICT in Developing CommunitiesExpert finding and Q&A systems