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Method for realizing user identity digitalization based on block chain

The invention discloses a method for realizing user identity digitalization based on a block chain. The method comprises the following steps: S1, monitoring a state of an API registration port; S2, inputting identity information; S3, performing identity information authentication, i.e., checking user identities through a police real name authentication system and bankcard binding mode according to information input by users in a registrant name input window, a registrant identity card number input window and a bank card number input window; S4, registering a platform account, and distributing block chain identities to the users; S5, setting a payment password; and S6, performing platform transaction. The method is a digital transaction method under the support of a block chain technology. According to the invention, under the technical support of a third-party service platform, the block chain identities can be provided for the users, it is ensured that the users can carry out digital economic transaction under the block chain technology, the security and the confidentiality are quite high, the transaction content cannot be tampered, traceability can also be performed in case of a transaction problem, and the transaction reliability is improved.
Owner:北京金股链科技有限公司

Commodity similarity calculation method and commodity recommending system based on image similarity

The invention relates to the field of internet electronic commerce, in particular to a commodity similarity calculation method and a commodity recommending system based on image similarity. The method includes: preprocessing a target image, to be specific, removing image differences caused by changes in light conditions such as brightness and chromatic aberration; processing the target image to detect a foreground frame; converting a community image in the foreground frame into pixel images different in scale by means of bilinear interpolation, and acquiring attribute features, in different dimensions, of the commodity image in the foreground frame under different scales; calculating attribute feature similarities, under different scales, between an attribute feature vector of the commodity image in the foreground frame and an attribute feature vector of a commodity sample image; according to a decision forest model and the attribute feature similarities under different scales, calculating commodity image similarities, under the pixel images of different scales, between the commodity image in the foreground frame and the commodity sample image; using the commodity image as a uniform identifier of a commodity on different commercial platforms. The commodity similarity calculation method and the commodity recommending system have the advantage that reliability of the system is greatly improved.
Owner:GUANGZHOU YUNCONG INFORMATION TECH CO LTD
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