Object processing method and device, electronic equipment and storage medium

Abstract

The invention discloses an object processing method and device, electronic equipment and a storage medium. The method comprises the steps that a push service request is acquired, and the push servicerequest carries a target object identifier of a to-be-pushed object; performing hash calculation on the target object identifier by adopting N hash functions to obtain N target hash values, wherein Nis an integer greater than or equal to 1; obtaining a target bitmap corresponding to the target object identifier; querying target data bits corresponding to the N target hash values from the target bitmap; and executing a processing operation on the to-be-pushed object according to the target parameter information displayed by the target data bit. According to the method, the parameters displayedby the data bits in the target bitmap are obtained through the hash value obtained by calculating the target object identifier, whether the to-be-pushed object is pushed or not can be quickly determined according to the parameters, the method is simple in operation, the algorithm has configurability, and the processing efficiency is higher when the data volume of the object is huge.

Description

technical field [0001] The present application relates to the field of data processing, and in particular to an object processing method, device, electronic equipment and storage medium. Background technique [0002] The rapid development of the Internet industry has brought explosive growth in content. In order to help users obtain information effectively, the personalized push system is playing an increasingly important role. Collaborative filtering technology is a kind of technology that has received wide attention in the push system. Different from traditional content-based direct filtering and analysis to push, collaborative filtering uses a large amount of user information to select users similar to the target user or items similar to the target item to finally push items that the current target user may be interested in. [0003] To analyze whether two items are the same in the existing technology, the current related algorithms are: [0004] (1) Euclidean algorith...

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Problems solved by technology

[0006] In the process of implementing the present application, the inventor found that the above-mentioned related algorithms for analyzing whether the items are the same in the prior art have the following defects: the amount of calculation is large and complex; the algorithm is relatively fixed and not configurable; therefore, the amount of data in the items is huge When the processing performance is low

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