人工智能/猜测用户服装品味的规则
是否有围绕人工智能的标准规则引擎/算法可以预测用户对特定类型产品（如衣服）的品味。 我知道这是所有电子商务网站都会为之奋斗的一件事。但我正在寻找那里定义的理论模式，这将有助于以更好的方式做出预测，即使不准确。
Are there standard rules engine/algorithms around AI that would predict the user taste on a particular kind of product like clothes.
I know it's one thing all e-commerce website will kill for. But I am looking out for theoretical patterns defined out there which would help make that prediction in a better way, if not accurately.
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两本介绍推荐系统的书：
基本上有两种解决问题的方法，基于用户或基于项目。 Netflix 似乎使用前者，而亚马逊则使用后者。通常，基于用户需要更多的时间和/或处理能力来生成推荐，因为您往往拥有比要考虑的项目更多的用户。
Two books that cover recommender systems:
Basically two ways of approaching the problem, user or item based. Netflix appears to use the former, while Amazon the latter. Typically user based requires more time and/or processing power to generate recommendations because you tend to have more users than items to consider.
不知道如何回答这个问题，因为这个问题太宽泛了。您所描述的是一种机器学习类型的任务，因此属于该（非常广泛的）保护范围。有许多不同的算法可用于类似的事情，但大多数文本会告诉您问题的定义是重要的部分。
时尚的哪些部分很重要？哪些部分不是？您将如何收集数据？数据的噪音有多大？所有这些都是问题空间的重要考虑因素。潘多拉在音乐方面做了类似的事情，其最大的好处是用户首先告诉他们他们喜欢什么和不喜欢什么。
为了对他们的音乐进行分类，他们实际上训练了音乐家听音乐来识别各种东西。请参阅 Ars Technica 上的文章 此处了解更多相关信息。根据我对时尚品味的了解，我想说这是一个类似的问题空间，并且可能需要专家“整理”信息，然后才能尝试进行比较。
很抱歉回答含糊不清 - 如果您想要更多具体信息，我建议您提出一个更具体的问题，有关特定算法或数据集等。
Not sure how to answer this, as this question is overly broad. What you are describing is a Machine Learning kind of task, and thus would fall under that (very broad) umbrella. There are a number of different algorithms that can be used for something like this, but most texts would tell you that the definition of the problem is the important part.
What parts of fashion are important? What parts are not? How are you going to gather the data? How noisy is the data? All of these are important considerations to the problem space. Pandora does a similar type of thing with music, with their big benefit being that their users tell them initially what they like and don't like.
To categorize their music, they actually have trained musicians listening to the music to identify all sorts of stuff. See the article on Ars Technica here for more information about that. Based on what I know about fashion tastes, I would say that it is a similar problem space, and would probably require experts to "codify" the information before you could attempt to draw parallels.
Sorry for the vague answer - if you want more specifics, I would recommend asking a more specific question, about specific algorithms or data sets, etc.