Restaurant mixed sorting method of take-out platform

Abstract

The invention discloses a restaurant mixed sorting method of a take-out platform. The method comprehensively considers factors such as restaurant order sales volume in recent time periods of the take-out platform, operation cooperation with merchants, personal preference of users and the like, and realizes sorting recommendation of restaurants nearby the users based on technologies such as data statistics and singular value decomposition. The method comprises the following steps: firstly, maintaining and supplementing data of all restaurants in a database, including setting operation weight and marking cuisine classification; secondly, analyzing and modeling recent orders: 1, determining restaurant order sales volume in different time periods, and 2, calculating cuisine preference of the user by using an SVD matrix decomposition algorithm; and then, ranking and displaying the restaurants near the users by comprehensively considering factors such as the state of the restaurants, the distance from the users, the operation weight, the time-phased order sales volume, the time when the users browse the platform, the cuisine preference and the like. Related data of a certain take-out platform is used for testing so as to verify that the method facilitates improvement of the click rate and the order conversion rate.

Description

technical field [0001] The invention relates to the field of network information technology, in particular to a method for mixing and sorting restaurants on a takeaway platform. Background technique [0002] The ranking effect of restaurants on the food delivery platform will directly affect the user experience, merchant sales and platform revenue. In terms of restaurant ranking and recommendation, the platform generally considers the following two aspects. One is to start from the user's point of view and use statistics and machine learning related algorithms to give priority to displaying higher sales and users who may like it and then place an order in the restaurant ranking process. restaurant, so as to improve user experience and platform orders; the other is from the perspective of platform operation, mainly considering whether the restaurant purchases advertisements on the platform, the current discount strength of the restaurant, the quality of the restaurant, and th...

AI Technical Summary

Problems solved by technology

In practical applications, if the ranking is only considered from the perspective of users, the platform will lose control over the ranking of restaurants, which is not conducive to the business development and traffic guidance of the platform and merchants; similarly, if only from the perspective of operation, it will affect the user's Browsing experience and order conversion rate, etc.

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