Method and a device for recommending the geographical position of a merchant store

Abstract

The invention discloses a method and a device for recommending the geographical position of a merchant store. The method comprises the following steps: acquiring the first user group feature of the historical consumer user group of the merchant; extracting the seed feature and the eigenvalue of the seed feature from the first user group feature; Analyzing a second user group characteristic of a user group in each target geographic region, and calculating eigenvalues of the second user group characteristics corresponding to each target geographic region; Matching the seed features with the features of the second user groups corresponding to each target geographic area, and calculating the recommended scores of each target geographic area by using the eigenvalues of the matching seed features and the eigenvalues of the features of the second user groups; According to the recommended scores of each target geographic area, the geographic location of the store is recommended to the merchants, and the recommended scores reflect the matching situation between the user groups in each target geographic area and the historical consumer user groups of the merchants.The recommended geographiclocation is more objective and scientific, and can ensure the flow and profitability of the merchants.

Description

technical field [0001] The present invention relates to the field of computer technology, in particular to a method and device for recommending the geographic location of a business store. Background technique [0002] In the offline business form, store location selection is a very important behavior for merchants, which will affect the positioning of the store, the type of products and the effect of operation. In the past, store location selection was basically based on the flow of people and the surrounding business form. For store selection, send observers to observe the flow of people, use questionnaires to look at the characteristics of the surrounding crowd, and then select the location of the store. However, a lot of people flow does not mean that they are all potential consumer groups of the store. Making decisions and judgments can lead to major mistakes. [0003] In order to solve the above problems, the Chinese patent application with the application publication...

AI Technical Summary

Problems solved by technology

[0002] In the offline business form, store location selection is a very important behavior for merchants, which will affect the positioning of the store, the type of products and the effect of operation. In the past, store location selection was basically based on the flow of people and the surrounding business form. For store selection, send observers to observe the flow of people, use questionnaires to look at the characteristics of the surrounding crowd, and then select the location of the store. However, a lot of people flow does not mean that they are all potential consumer groups of the store. Making decisions and judgments can lead to major mistakes

[0003] In order to solve the above problems, the Chinese patent application with the application publication number CN 106294516A discloses a method and device for providing location information, which mainly utilizes merchants to position themselves, such as keywords "white-collar", "high-frequency medium-sized ", to determine the characteristics of the target user, after determining the first area (wherein the first area includes a plurality of second areas), according to the location information of the users in the first area, determine the users with the characteristics of the target user in each second area The second number of users, according to the second number of users, determine the index value of the target user feature in each second area; sort the multiple second areas according to the index value; use the second area with the top M positions in the sorting result as a candidate area, The candidate area is provided to the first user. This method of determination will result in an inaccurate recommended geographic location due to inaccurate positioning of the business, and it is impossible to recommend the geographic location objectively and scientifically. In addition, the candidate area provided is only It is in line with the positioning set by the merchant itself, and cannot guarantee the user flow of the merchant at the consumption level

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