Recommendation method based on situation fusion sensing

The invention provides a recommendation method based on situation fusion sensing. The recommendation method comprises the following steps that 1, the situation is divided into physical situations and user preference situations according to the definition and the requirements of the situations; 2, a Bayes network is built through parameter learning and structure learning, and the physical situation matching degree in a certain environment is ratiocinated and calculated; 3, through considering the dynamics of hobbies and interests of users along with the time change, a time function is merged into a recommendation algorithm based on the content, and the matching degree of the user preference situation is calculated; 4, the situation matching degree is comprehensively considered, all candidate information resources are graded, and in addition, information ranking in first Top-N is recommended to target users. Compared with the prior art, the recommendation method provided by the invention has the advantages that the considered recommendation factors are more comprehensive, the method can better adapt to changeful environment, the recommendation accuracy is improved, in addition, the condition that the interest of the users is changed along with the time change is considered, the time function is combined with the recommendation based on the resource content, and the user satisfaction degree is improved.