The invention relates to an item information recommending method based on user network data. The method is characterized by including the following steps of firstly, obtaining item demand information of a user through the user network data, and setting up a user demand feature library; secondly, setting up an item information feature library according to item network data; thirdly, matching the user demand features with the item information features through a text and semantic similarity algorithm, calculating the similarity between item information and user demands, conducting sequencing and filtering, and finally generating the recommending result; fourthly, feeding the generated recommending result back to the user demand feature library and the item information feature library, and conducting training and renewing. Compared with the prior art, the method has the advantages of being comprehensive in information, wide in application range and the like.