如何解决 AWS 个性化中的 Multi_vendor 问题? [英] How to solve Multi_vendor problem in AWS personalize?

问题描述

我正在使用 AWS 个性化 来制作推荐系统，特别是 SIMS 模型(项目到项目的相似性模型)所以当我输入 ITEM_ID 输出 将是最相似项目的列表.直到现在事情都非常顺利，但是:

I am using AWS personalize for making a recommendation system, specifically SIMS model (item to item similarities model) so when I input ITEM_ID the output will be a list of the most similar items. until now things are very smooth but:

现在我有很多 SELLER_ID 礼物，因为它是一个电子商务应用程序不仅仅是一家商店.这里的问题是我希望仅针对用户所在的商店进行推荐.例如:我想要推荐 [rec1,rec2,....etc] 仅在商店中可用的商品，而不是其他商店，就好像您在商店 STR0003 中一样，然后您希望来自商店的推荐 STR0003 仅不存储 STR0005 或 STR0006.

now I have many SELLER_ID presents as it is an e-commerce application not only one store. the problem here is that I want recommendations only for the store the user in. For instance: I want recommendations [rec1,rec2,....etc] for item only available in a store, not other stores as if you are in store STR0003 then you want recommendations from store STR0003 only not store STR0005 or STR0006.

我尝试了很多解决方案，但每个人都遇到了麻烦:

I have tried many solutions but in everyone I am facing hassles:

解决方案 1:

在 ITEMS.csv 数据中添加 SELLER_ID 作为元数据:SELLER_ID 列将用于每一行:[STR0001|STR0002|...]然后使用 filter 根据 SELLER_ID 过滤结果:我输入 STR0003 然后输出该商店中可用的项目.

add SELLER_ID as metadata in ITEMS.csv data : SELLER_ID column will be for each row :[STR0001|STR0002|...] and then using a filter to filter results depending on the SELLER_ID: I enter STR0003 then output items available in that store.

• 问题 1:字符限制为 1024，某些产品在 200 家商店中存在，因此无法将字符减少到 1024，(即使使用正则表达式).

• problem1 : characters are limited to 1024, some products present in 200 stores which make it impossible to reduce characters to 1024,(even using regex).

问题2:我们怀疑过滤器是，不是免费的！我们为此付出代价.我搜索了许多文档以查看过滤器是免费的还是付费的，但没有找到.

problem2 : we suspect that filters are , not free! we pay for it. I searched for many docs to see if filters are free or paid but didn't find any.

解决方案 2:

在 INTERACTION.csv 中添加 SELLER_ID 作为元数据，以便将其包含在 get_recommendations 和输出结果的 context={} 中.

adding SELLER_ID as metadata in INTERACTION.csv so including it in context={} in get_recommendations and output results.

• 该解决方案中的问题:

在我的数据中.我的数据中没有足够的 SELLER_ID 来包含 INTERACTION.csv 中的每一行.

in my data. I don't have sufficient SELLER_ID in my data to include for each row in INTERACTION.csv.

我想问是否有人遇到过多供应商推荐的问题.他/她如何解决这个问题，解决这个问题的最佳方法是什么?还免费使用过滤器吗?

I am asking if anyone faced the problem of MULTI VENDOR RECOMMENDATION. how could he/she solve it and what is the best approach for this problem? also is using filters free?

提前致谢

推荐答案

Personalize 通过 数据集组.您将为每个租户/供应商/卖方创建一个单独的数据集组，然后将交互、项目和用户上传和/或流式传输到每个租户的数据集组的适当数据集中.每个租户也将拥有自己的解决方案和活动.数据集组为您提供在此类系统中运行业务的客户所期望的必要租户隔离，以及为每个租户设置和自定义架构、解决方案、过滤器和活动的灵活性.

Personalize supports these types of multi-tenant deployment models through dataset groups. You would create a separate dataset group for each tenant/vendor/seller and then upload and/or stream interactions, items, and users into the appropriate datasets for each tenant's dataset group. Each tenant will have their own solutions and campaigns as well. Dataset groups give you the necessary tenant isolation expected by customers running their businesses in this type of system as well as the flexibility to setup and customize schemas, solutions, filters, and campaigns for each of your tenants.

请注意，Personalize 的默认配额/限制专为单个客户/租户配置而设计，但可以在 AWS 控制台中请求增加限制，或通过支持扩展支持数百个供应商的多租户模型，如您所述.

Note that the default quotas/limits for Personalize are designed for the single customer/tenant configuration but limit increases can be requested in the AWS console or through support to scale a multi-tenant model supporting hundreds vendors as you described.

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