The invention relates to a multi-feature-combined Hash information retrieval method. The method is characterized by comprising the following basic steps that 1, an objective function is set up, data distribution of an object space is protected, compact matrix basis in an NMF is obtained, and redundancy is reduced; 2, alternative optimization is carried out, U and V are optimized through an iterative process, and updating rules of the base operator U and low-dimension data V are obtained; 3, global convergence is carried out, and alternating iteration is carried out through the original objective function; 4, a Hash function is generated, and finial results are obtained by calculating the hamming distance between training data and a test sample, namely XOR operation; 5, complexity analysis is carried out on the methods in the step 1 to step 4. By means of the method, probability distribution of data can be effectively protected, redundancy of low-dimension data is reduced, and therefore a Hash embedded function can be learned, wherein through the Hash embedded function, multiple expressions obtained from multiple sources can be fused, and RKNMF can be used for protecting high-dimension joint distribution and obtaining orthogonal basis.