Abstract: A knowledge graph-based method for recommending traditional Chinese medicine (TCM) prescriptions is provided. The method integrates a knowledge graph embedding model, a multi-head attention mechanism, graph convolutions, and other techniques to combine graph features with a recommendation system, for comprehensively considering patient conditions to recommend TCM prescription. Taking TCM case description texts as the research object and integrating with TCM knowledge graph information, the method draws from the clinical experience of renowned TCM experts and fully considers various individual factors such as medicinal properties, efficacy, medical conditions, and patient constitutions. Based on the holistic principles of TCM and the ideology of syndrome differentiation and treatment, the method selects different herbal combinations based on varying symptoms and medical conditions of patients.

Abstract: A production task scheduling method, system and device for a flexible assembly job shop is provided.