复杂层次结构建模
为了获得一些经验，我正在尝试制作一个可以回答有关动物王国的查询的专家系统。但是，我遇到了域建模问题。我最初认为动物王国的层次结构可以这样绘制，
-animal
-bird
-carnivore
-hawk
-herbivore
-bluejay
-mammals
-carnivores
-herbivores
我认为这样可以让我轻松地进行查询，例如“给我所有鸟类”，但说“给我所有食肉动物”会更昂贵，所以我将层次结构重写为看起来像：
-animal
-carnivore
-birds
-hawk
-mammals
-xyz
-herbivores
-birds
-bluejay
-mammals
但是现在查询“给我所有的鸟”会慢得多。
这当然是一个简单的例子，但它让我想到，在编写专家系统来回答上述查询的情况下，我真的不知道如何对本质上不那么严格分层的复杂关系进行建模。有向循环图似乎可以在数学上解决问题，但将其存储在关系数据库中并维护它（更新）对我来说似乎是一场噩梦。我想知道人们通常如何建模此类事物。解释或指向进一步阅读的资源的指针将是可以接受和赞赏的。
To gain some experience, I am trying to make an expert system that can answer queries about the animal kingdom. However, I have run into a problem modeling the domain. I originally considered the animal kingdom hierarchy to be drawn like
-animal
-bird
-carnivore
-hawk
-herbivore
-bluejay
-mammals
-carnivores
-herbivores
This I figured would allow me to make queries easily like "give me all birds", but would be much more expensive to say "give me all carnivores", so I rewrote the hierarchy to look like:
-animal
-carnivore
-birds
-hawk
-mammals
-xyz
-herbivores
-birds
-bluejay
-mammals
But now it will be much slower to query "give me all birds."
This is of course a simple example, but it got me thinking that I don't really know how to model complex relationships that are not so strictly hierarchical in nature in the context of writing an expert system to answer queries as stated above. A directed, cyclic graph seems like it could mathematically solve the problem, but storing this in a relational database and maintaining it (updates) would seem like a nightmare to me. I would like to know how people typically model such things. Explanations or pointers to resources to read further would be acceptable and appreciated.
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您遇到了分类法的问题之一（事实上，远不是唯一的问题，甚至不是最糟糕的问题）。 多重继承作为一种概念工具，避免了分类法的许多问题 - 另一种说法是，分类法定义一棵树，基于 MI 的分类方案定义更通用的有向无环图，并且因此为您的建模提供了额外的自由度。
关系数据库方法会有所不同（不具体考虑层次结构或继承），但会得出与“多重继承”大致相同的概念结果：“类”（在林奈意义上的门/类/目/族/属/物种）是记录的一个领域，饮食（食肉动物、草食动物、杂食动物）是一个独特的领域——它们在概念化和搜索/检索方面都不会相互限制。
如果您被迫使用限制分类法的工具（又名树、单一继承等）进行建模，那么有一些技巧可以减轻它们造成的痛苦（在一定程度上），但它们取决于每个工具的具体情况限制，所以很难一概而论。
You've hit upon one of the problems with taxonomies (far from the only one, or even the worst one, in fact). Multiple Inheritance as a conceptual tool avoids many of the problems with taxonomies -- another way of putting it is, a taxonomy defines a tree, a MI-based classification scheme defines a more general directed acyclic graph, and therefore affords extra degrees of freedom in your modeling.
A relational database approach would be different (not thinking of hierarchy or inheritance specifically) but come to much the same conceptual results as "multiple inheritance": the "class" (in the Linnaeus sense of phylum/class/order/family/genus/species) is one field of the record, the diet (carnivore, herbivore, omnivore) a distinct one -- they don't constrain each other, neither in conceptualization nor in searches / retrieval.
If you're forced to model with tools that restrict you to taxonomies (AKA trees, single inheritance, &c), there are some tricks to ameliorate the pain they cause (to a modest degree), but they depend on each tool's specific restrictions, so it's hard to generalize.
如果您查看 MongoDB 手册页 使用多键模拟大量索引，你会看到MongoDB会让你在它的数据库中为每一种动物创建一个包含各种信息的“文档”：
然后你就可以查找通过您想要的属性的任意组合！
If you take a look at the MongoDB manual page on Using Multikeys to Simulate a Large Number of Indexes, you will see that MongoDB would let you create one "document" in its database for each animal that contains all sorts of information:
Then you can look up by any combination of attributes you want!
我使用 图数据库后端。我使用的示例最初来自 这个 基于 SQL 的示例。现在我什至不会尝试使用 SQL 来解决此类问题，这太痛苦了。 （免责声明：我是 Neo4j graphdb 团队的成员）
I wrote up a user roles example using a similar problem with a Graph database back-end. The example I use originally comes from this SQL based example. I wouldn't even try using SQL for this kind of problem nowadays, it's such a pain. (disclaimer: I'm on the Neo4j graphdb team)