The invention discloses a recommended 
system and a method with facing 
social network for 
context awareness based on the 
tensor decomposition, and relates to the field of the 
data mining and the 
information retrieval. Firstly, the method makes use of a 
social network massive 
data set to collect users and projects and contexts, to pay attention to the 
list information, to establish an original the user-the project-the context mark matrix, to calculate the users similarity, and to establish a user-user 
similarity matrix; Secondly, aim at the extreme sparsity of the original mark matrix, a sparse mark matrix is predicated and filled by using the 
tensor decomposition; Thirdly, aim at a problem that the user 
similarity matrix is sparse, a sparse user 
similarity matrix is predicated and filled by using the 
matrix decomposition; Finally, according to some similar interest tendencies of some similar users in the 
social network, a social normalization item is taken to optimizing the mark matrix. The method deals with the problem that a traditional predicated mark matrix does not consider that the context information and the relationship between users have an effect on marking. Also, the method deals with an obstruction which is caused by the sparsity of the mark matrix brings to the recommended 
system, thus the accuracy of the recommended 
system is improved. The method can be widely applied to the fields of the social network, the electronic commerce and the like.