Data acquisition method, device and system and computer storage medium

Abstract

The embodiment of the invention provides a data acquisition method and device. The device comprises at least one data acquisition module; different data acquisition modules correspond to different data acquisition algorithms. The device further comprises a determination module used for determining at least one target data acquisition module corresponding to a target service type in the at least two service types; the target data acquisition module corresponds to at least one target user feature identifier and at least one target index identifier; the user feature management module is used for acquiring target first user features corresponding to the at least one target user feature identifier; and the index management module is used for accessing indexes corresponding to the at least one target index identifier according to the target first user feature to obtain a first data set. According to the embodiment of the invention, a plurality of processing logics in a traditional data acquisition architecture are decoupled, the design accords with an opening and closing principle, the code reuse rate is high, and the expansion is easy.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a data acquisition method, device, system and computer storage medium. Background technique [0002] With the development of information technology, people have gradually entered the era of information overload. In order to solve the problem that users want to find the information they are interested in from a large amount of information, and information producers want the information they produce to get attention, the recommendation system came into being. The recommendation system needs to explore the user's behavior and find out the user's individual needs, so as to accurately recommend the information that the user needs to the user. [0003] Recommender systems involve two key issues, recall and ranking. Among them, recall refers to triggering as many correct results (that is, recalled data) as possible from the original data (generally understood as a full set o...

AI Technical Summary

Problems solved by technology

The design violates the principle of opening and closing, modification can easily lead to ripple effects, the code reuse rate is low, and the new data acquisition module has a long development cycle, low efficiency, and cannot be flexibly expanded

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