Interactive product recommendation method and non-transitory computer-readable medium
A interactive product recommendation method is provided, including: selecting a target product from the plurality of products; loading the product information of the target product; generating a product list according to the product characteristics corresponding to the target product and the user preferences corresponding to at least one user; generating a first label list based on at least one product characteristics corresponding to the target product and the user preferences corresponding to the user, where the first label list has a plurality of first labels corresponding to different product features; and displaying the product information, the product list and the first label list in a user interface. When clicking the icon, displaying another user interface corresponding to the clicked icon. When clicking the first label, updating the product list according to the clicked first label.
1. An interactive product recommendation method, performed by a processor of an electronic device, comprising:
choosing a target product from a plurality of products;
loading product information corresponding to the target product;
generating a product list having a plurality of icons corresponding to different products based on correlations between the products and a user preference corresponding to at least one user;
generating a first tag list based on at least one product characteristic of the target product and the user preference corresponding to at least one user, wherein the first tag list includes a plurality of first tags identifying different product features, wherein the plurality of first tags comprise at least one first expandable tag corresponding to the product features;
displaying the product information, the product list, and the first tag list through a first user interface;
detecting a click on one of the icons in the product list;
loading and displaying a second user interface having product information corresponding to the clicked icon;
detecting a click on one of the first tags in the first tag list;
updating the product list based on the clicked first tag;
displaying the updated product list;
calculating a score for every two product features based on a behavior-based association analysis method according to a historical record corresponding to one of said users;
filtering, based on a threshold, the product features according to the score to generate a first sub-tag list;
detecting a click on the first expandable tag; and
loading and displaying the first sub-tag list when the first expandable tag is clicked.
2. The interactive product recommendation method as claimed in claim 1 , further comprising:
generating a second tag list based on preferred customer characteristics corresponding to the target product, wherein the second tag list has a plurality of second tags corresponding to different target customer characteristics.
3. The interactive product recommendation method as claimed in claim 2 , further comprising:
updating the product list and the first tag list according to a clicked second tag when any of the second tags is clicked.
4. The interactive product recommendation method as claimed in claim 1 , wherein the first sub-tag list comprises a plurality of first sub-tags having the same type but different attributes.
5. The interactive product recommendation method as claimed in claim 1 , further comprising:
updating the product list according to a clicked first sub-tag when any of the first sub-tags is clicked.
6. The interactive product recommendation method as claimed in claim 1 , further comprising:
filtering the product features relative to the target product according to a behavior-based association analysis method or a content-based association analysis method.
7. The interactive product recommendation method as claimed in claim 1 , further comprising:
updating the user preferences according to a click behavior and/or one purchase behavior of the user.
8. The interactive product recommendation method as claimed in claim 1 , wherein the product features comprise a brand, a product name, materials, a size, product efficacies, a price and/or a preference group characteristic.
9. The interactive product recommendation method as claimed in claim 8 , wherein the preference group characteristics comprise gender, age group and/or residential area.
10. A non-transitory computer-readable medium having instructions stored therein, when the instructions are executed by a processor of an electronic device, operations performed by the electronic device comprise:
choosing a target product from a plurality of products;
loading product information corresponding to the target product;
generating a product list having a plurality of icons corresponding to different products based on correlations between the products and a user preference corresponding to at least one user;
generating a first tag list based on at least one product characteristic of the target product and the user preference corresponding to at least one user, wherein the first tag list includes a plurality of first tags identifying different product features, wherein the plurality of first tags comprise at least one first expandable tag corresponding to the product features;
displaying the product information, the product list, and the first tag list through a first user interface;
loading and displaying a second user interface having product information corresponding to a clicked icon when any of the icons in the product list is clicked;
updating the product list based on a clicked first tag when any of the first tags in the first tag list is clicked;
displaying the updated product list;
calculating a score for every two product features based on a behavior-based association analysis method according to a historical record corresponding to one of said users;
filtering, based on a threshold, the product features according to the score to generate a first sub-tag list; and
loading and displaying the first sub-tag list when the first expandable tag is clicked.
11. The non-transitory computer-readable medium as claimed in claim 10 , wherein the operations performed by the electronic device further comprise:
generating a second tag list based on preferred customer characteristics corresponding to the target product, wherein the second tag list has a plurality of second tags corresponding to different target customer characteristics.
12. The non-transitory computer-readable medium as claimed in claim 11 , wherein the operations performed by the electronic device further comprise:
updating the product list and the first tag list according to a clicked second tag when any of the second tags is clicked.
13. The non-transitory computer-readable medium as claimed in claim 10 , wherein the first sub-tag list comprises a plurality of first sub-tags having the same type but different attributes.
14. The non-transitory computer-readable medium as claimed in claim 10 , wherein the operations performed by the electronic device further comprise:
updating the product list according to a clicked first sub-tag when any of the first sub-tags is clicked.
15. The non-transitory computer-readable medium as claimed in claim 10 , wherein the operations performed by the electronic device further comprise:
filtering the product features relative to the target product according to a behavior-based association analysis method or a content-based association analysis method.
16. The non-transitory computer-readable medium as claimed in claim 10 , wherein the operations performed by the electronic device further comprise:
updating the user preferences according to a click behavior and/or one purchase behavior of the user.
17. The non-transitory computer-readable medium as claimed in claim 10 , wherein the product features comprise a brand, a product name, a material, a size, a product efficacy, a price and/or a preference group characteristic.
18. The non-transitory computer-readable medium as claimed in claim 17 , wherein the preference group characteristics comprise gender, age group and/or residential area.