Design and implementation of a recommendation system for improved crop varieties based on Knowledge Graph
Seeds are the foundation of agricultural production.By scientifically evaluating factors such as crop variety adaptability,yield potential,quality characteristics,and resistance,selecting excellent varieties suitable for local ecological environments and market demands is of great significance for improving agricultural production efficiency,promoting rural economic development,and increasing farmers'income.Therefore,based on knowledge graph technology,this paper constructs a crop variety QA system to help farmers quickly and accurately obtain relevant information on crop varietie.First,this paper collects relevant data on crop varieties,including variety names,sources,growth cycles,suitable planting regions,and disease stages.Secondly,knowledge graph of crop varieties is constructed using data preprocessing,knowledge fusion,and knowledge storage methods.Then,a QA system is designed and developed using natural language processing and BiLSTM-CRF technology.Finally,the crop variety QA system constructed in this paper has an accuracy rate of 87.67％according to testing,and can meet users'requirements for querying,obtaining,and recommending information on crop varieties.
万方数据
维普
