Hello, brain matching engine 2.0 has added "intelligent recommendation assistant"
* * * Enjoying travel has penetrated into people's lives. Hitchhiking, a mode of equality, mutual assistance and sharing, not only improves the convenience of people's travel, but also reduces the travel cost of both drivers and passengers. However, when both drivers and passengers use hitchhiking service, there are usually many identical trips. When the number of simultaneous orders is large, the back-end server needs to calculate the matching party corresponding to each order in time. For frequent drivers and passengers, service matching will have a certain lag, which will indirectly affect the user experience.
The invention of "a service business matching method, device, computer equipment and storage medium" aims to analyze and obtain the travel characteristics of both drivers and passengers through their historical billing behaviors, dynamically calculate the travel behavior at the next moment, and intelligently recommend the car owners or passengers on the way, which is equivalent to the "intelligent recommendation assistant" of platform users.
It is understood that at present, the backstage of Harbin SF receives a huge amount of travel data every day. Patents allow the background to effectively filter out trips with high correlation through geographic information; And the matching results are calculated by the Hello brain matching engine at the level of 2.0 seconds, and recommended to drivers and passengers respectively.
According to the prospectus submitted by Hello Bike on April 24th, in 2020, the total transaction volume of Hello Free Ride will be 7 billion yuan, making it the second largest free ride trading platform in China. By the end of 2020, Hello SF has accumulated 2,665,438+users and nearly 10 million registered drivers.
Forecast the supply-demand ratio of power grid and conduct capacity scheduling.
The invention of "processing method, device, computer equipment, storage medium and vehicle dispatching system" aims to solve the problem of supply and demand balance in different areas of Hello taxi, and can predict supply and demand and balance capacity based on deep learning, so that users in all areas can get a taxi faster. At present, Hello taxi business has been launched in Zhongshan, Huizhou, Heyuan, Shanwei and other places in Guangdong Province.
In this patent, the background of Hello taxi divides the operation area into several grids. Through neural network model and deep learning, the orders, capacity and road conditions of different grids at a certain moment are considered, so as to predict the supply-demand ratio of each grid in a certain time period in the future, and conduct certain supply-demand intervention behaviors according to the supply-demand ratio, such as price intervention, capacity scheduling, marketing intervention, etc.
Patents match supply and demand from multiple dimensions. In the process of supply and demand matching, the driver's position is reported in real time and immediately uploaded to Hello Brain Matching Engine 2.0. At a certain moment, passengers initiate a travel request from A to B, and the data obtained in the background will be matched with the drivers selected in the pool immediately according to certain conditions. The factors to be considered in the matching include distance, passing distance, real-time road conditions, passenger characteristics and preferences, driver registration characteristics and platform behavior characteristics, and the whole matching process is completed within 200 milliseconds.
There is also personalized feature matching behind driver-passenger matching. For example, individual users may only like a certain type of car and a certain type of driver. Female users may have higher requirements for models and drivers at eleven or twelve in the middle of the night and need personalized matching.
Author: Xiao-ming zhang