Real-time matching method

Abstract

The invention discloses a real-time matching method. The real-time matching method is implemented by a system resource management function module, a state management and maintenance function module, a matching computation function module and the like and includes enabling a system to build data models of user objects; storing the modeled user objects in a data structure of a memory; scheduling and shifting the objects and changing states of the objects by a scheduling algorithm; performing scanning and matching computation on the user objects in matching queues according to a matching computation algorithm and matching parameters; updating queue states of the user objects and counting various matching dynamic parameters of the user objects after the user objects are subjected to matching computation; performing the matching algorithm and dynamically adjusting the parameters to adjust integral user resource scheduling for a next computation matching cycle. The data structure contains the queues, lists, arrays and the like. The dynamic parameters include success rates, available system resources and the like. The real-time matching method has the advantage that a core resource scheduling and matching algorithm can be provided for the real-time computation car-sharing application system by a real-time computation matching car-sharing algorithm.

Description

technical field [0001] The invention relates to the technical field of mobile communication and software, in particular to a real-time matching method. Background technique [0002] With the development of Internet technology and communication technology, especially the development of intelligent terminal and system software technology, a real-time matching method is provided. [0003] At present, with the development of urban life, the shortage of taxi resources, and the rising cost, carpooling has become a popular way of life for users, but the current matching methods do not meet people's needs well, mainly based on artificial or The network releases information, the system does not match in real time, and the result takes a long time, or manual judgment and matching are performed. Common scenarios usually include a fixed starting point, such as the community where the user lives, which is not very good when the user's needs change frequently. Local adaptation, such as w...

AI Technical Summary

Problems solved by technology

[0003] At present, with the development of urban life, the shortage of taxi resources, and the rising cost, carpooling has become a popular way of life for users, but the current matching methods do not meet people's needs well, mainly based on artificial or The network releases information, the system does not match in real time, and the result takes a long time, or manual judgment and matching are performed. Common scenarios usually include a fixed starting point, such as the community where the user lives, which is not very good when the user's needs change frequently. Local adaptation, such as when the user moves to another starting location, the user needs to wait for resources again. In the entire carpooling process, there are still many manual steps. The use of users is cumbersome, and users cannot put forward various personalized requirements, such as time, place, gender, etc., and the mode is relatively single, which cannot meet the needs of many real-time or temporary scenarios

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