The invention discloses an employee individualized-learning recommendation method based on a learning map and collaborative filtering.The method includes the steps that resource features and employee attributes are respectively extracted according to the learning resource content of an online learning platform and the practical conditions of learners (enterprise employees), a mathematical model is built, a recommendation list is calculated according to similarity to generate the recommendation result, the feedback conditions of the learners are collected to be used for improving similarity calculation, and the recommendation process is optimized.The method has certain universality in recommending the content of semi-structured data, unstructured data and multimedia learning resources, the learning map of the employees and collaborative filtering are combined, the recommendation effect is corrected and optimized, the sparse scoring matrix and learning resource recommendation, namely, cold starting, of new employees can be effectively achieved, pushing of the learning content of the online learning platform is more user-friendly, the enterprise employees are effectively assisted in rapid growing, employee training and learning cost is saved, and employee learning efficiency is improved.