Product recommendation method and device for agricultural material e-commerce platform

Abstract

The invention discloses a product recommendation method and device for an agricultural material e-commerce platform. An association relationship of users' regions, seasons, and agricultural materialsis established; and agricultural products planted correspondingly at specific seasons in users' regions and agricultural material products with specific purposes at corresponding planting stages are obtained and the information is recommended to users, so that the characteristics of the agricultural material e-commerce platform are met well. The method comprises: according to region information and access time of a user, at least one first associated label group having a corresponding season interval and regional interval are obtained; according to a purpose label, a class label, and a crop label in the first associated label group, at least one corresponding first information label group is obtained; a corresponding product information list is screened out from a product base based on thefirst information label group; and according to a preset product sorting mechanism, the product information list is ranked to obtain a product recommendation order and the order is fed back to the user. In addition, the device is composed of a first acquiring module, a second acquiring module, a screening module, and a sorting module that are used for implementing the above-mentioned method.

Description

technical field

[0001] The invention relates to the field of software technology, in particular to a method and device for product recommendation. Background technique

[0002] The rapid development of e-commerce has led to more and more e-commerce platforms and more and more types of goods. Agriculture is the largest industry in my country, and the rapid development of agricultural materials e-commerce platforms is highly anticipated. As an important part of e-commerce, agricultural materials e-commerce has both the commonality of other e-commerce platforms and its own characteristics. It is the common goal of the majority of e-commerce companies to provide platform users with convenient product browsing and purchase payment. However, with the continuous expansion of e-commerce and the rapid increase in the variety and quantity of commodities, agricultural materials e-commerce, like many other e-commerce platforms, will inevitably experience the problem of user feedback "c...

Examples

Embodiment 1

[0056] Such as figure 1 As shown, the embodiment of the present invention provides a commodity recommendation method for an agricultural material e-commerce platform, the method comprising the following steps:

[0057] S101 According to the user's regional information and access time, acquire at least one first associated tag group with corresponding time season intervals and regional intervals.

[0058] Specifically, the association tag group includes a season interval, a region interval, a usage tag, a category tag, and a crop tag. There are multiple sets of associated tag groups at the same time. The geographical intervals are pre-divided and set according to the national geographical conditions, planting habits or characteristic planting areas. Season intervals are based on traditional solar terms and crop planting habits, dividing a year into several intervals. Multiple association label groups may have the same geographic interval but different seasonal intervals. Si...

Embodiment 2

[0078] This embodiment is a further optimization of Embodiment 1, and provides another product recommendation method for an agricultural materials e-commerce platform. The optimization in this embodiment is specifically as follows:

[0079] Such as figure 2 As shown, step S101 is a step of acquiring at least one first associated tag group with corresponding time season intervals and regional intervals according to the user's regional information and access time, specifically including:

[0080] S201 Obtain a forecasted time interval within a preset time period after the user's access time.

[0081] For example, if the user visits in February, the forecast period ranges from February to May.

[0082] S202 Screening a plurality of second associated label groups according to the predicted time season intervals, where the time season intervals in the second associated label groups and the predicted time season intervals include each other or completely overlap or partially overl...

Embodiment 3

[0090] Such as image 3 As shown, this embodiment is a further optimization of Embodiment 1, and provides another commodity recommendation method for an agricultural materials e-commerce platform. The method specifically includes the following steps:

[0091] S301 According to the historical behavior data, regional information, behavior time information of all historical users operating commodities, product information of operating commodities, and product names, category tags, usage tags, and crop tags corresponding to the product information, construct an associated tag group.

[0092] S302 According to the user's regional information and access time, acquire at least one first associated tag group with corresponding time season intervals and regional intervals.

[0093]S303 Acquire at least one corresponding first information tag group according to the usage tag, category tag, and crop tag in the first associated tag group.

[0094] S304 Filter out a corresponding commodit...

technical field

[0001] The invention relates to the field of software technology, in particular to a method and device for product recommendation. Background technique

[0002] The rapid development of e-commerce has led to more and more e-commerce platforms and more and more types of goods. Agriculture is the largest industry in my country, and the rapid development of agricultural materials e-commerce platforms is highly anticipated. As an important part of e-commerce, agricultural materials e-commerce has both the commonality of other e-commerce platforms and its own characteristics. It is the common goal of the majority of e-commerce companies to provide platform users with convenient product browsing and purchase payment. However, with the continuous expansion of e-commerce and the rapid increase in the variety and quantity of commodities, agricultural materials e-commerce, like many other e-commerce platforms, will inevitably experience the problem of user feedback "c...

Examples

Embodiment 1

[0056] Such as figure 1 As shown, the embodiment of the present invention provides a commodity recommendation method for an agricultural material e-commerce platform, the method comprising the following steps:

[0057] S101 According to the user's regional information and access time, acquire at least one first associated tag group with corresponding time season intervals and regional intervals.

[0058] Specifically, the association tag group includes a season interval, a region interval, a usage tag, a category tag, and a crop tag. There are multiple sets of associated tag groups at the same time. The geographical intervals are pre-divided and set according to the national geographical conditions, planting habits or characteristic planting areas. Season intervals are based on traditional solar terms and crop planting habits, dividing a year into several intervals. Multiple association label groups may have the same geographic interval but different seasonal intervals. Si...

Embodiment 2

[0078] This embodiment is a further optimization of Embodiment 1, and provides another product recommendation method for an agricultural materials e-commerce platform. The optimization in this embodiment is specifically as follows:

[0079] Such as figure 2 As shown, step S101 is a step of acquiring at least one first associated tag group with corresponding time season intervals and regional intervals according to the user's regional information and access time, specifically including:

[0080] S201 Obtain a forecasted time interval within a preset time period after the user's access time.

[0081] For example, if the user visits in February, the forecast period ranges from February to May.

[0082] S202 Screening a plurality of second associated label groups according to the predicted time season intervals, where the time season intervals in the second associated label groups and the predicted time season intervals include each other or completely overlap or partially overl...

Embodiment 3

[0090] Such as image 3 As shown, this embodiment is a further optimization of Embodiment 1, and provides another commodity recommendation method for an agricultural materials e-commerce platform. The method specifically includes the following steps:

[0091] S301 According to the historical behavior data, regional information, behavior time information of all historical users operating commodities, product information of operating commodities, and product names, category tags, usage tags, and crop tags corresponding to the product information, construct an associated tag group.

[0092] S302 According to the user's regional information and access time, acquire at least one first associated tag group with corresponding time season intervals and regional intervals.

[0093]S303 Acquire at least one corresponding first information tag group according to the usage tag, category tag, and crop tag in the first associated tag group.

[0094] S304 Filter out a corresponding commodit...

Images