Knowledge-Based Recommendation System for Plate Waste Reduction in Latvian Schools

Food waste indicates ineffective and irresponsible consumption of resources, particularly during the food consumption stage. The aim of our research study is to optimize the catering management process at Latvian schools by reducing the amount of plate waste. The experts developed a set of recommendations aimed at improving the catering management process at schools. The recommendations developed were supported by measurable parameters, which must be monitored by school staff. The capability-driven development approach was applied to model the recommendation system. A plate waste predictive module and a large language model classifier were integrated into the system to support sustainable decision-making. The large language model classifier was trained to filter questions and recommendations. Three training methods were compared: training from scratch and finetuning by using datasets DBPedia and News Category Dataset. As a result, we present the list of recommendations based on the literature review, and the prototype of the knowledge-based recommendation system was developed to audit the school catering management process and promote sustainable school management and decision-making. The recommendation system aims to reduce plate waste due to deficiencies in the implementation of the catering process and to promote responsible food consumption at schools.