Personalized recommendation method

The invention discloses a personalized recommendation method. The method comprises the following steps of: acquiring basic data; processing and classifying the basic data, and analyzing the interest and preference of a purchaser on the basis of historic operation behavior records of the purchaser; filtering and collecting seller information and product information according to a preset rule; correspondingly acquiring a set of products to be recommended according to the interest and preference data information of the purchaser, the seller information and the product information on the basis of a preset matching algorithm; de-duplicating, sorting, weighting and standardizing all products to be recommended, and thus obtaining N optimally-matched products which serve as a recommendation result; and displaying the final recommendation result to the purchaser. By adoption of the personalized recommendation method, the product information which is in accordance with the interest and preference of a user can be accurately recommended to the user in the conventional electronic-commerce business-to-business (B2B) website.