DL Reasoner 与规则引擎：您能解释一下区别吗？
有人可以解释像 Pellet/默认 OWL Reasoner 这样的 DL Reasoner 和像 Jess 这样的规则引擎之间的区别吗？及其应用？
谢谢。
Can someone explain the differences between a DL Reasoner like Pellet/deafult OWL Reasoner and a rule engine like Jess? and their applications ?
Thanks.
如果你对这篇内容有疑问，欢迎到本站社区发帖提问 参与讨论，获取更多帮助，或者扫码二维码加入 Web 技术交流群。
绑定邮箱获取回复消息
由于您还没有绑定你的真实邮箱，如果其他用户或者作者回复了您的评论，将不能在第一时间通知您！
发布评论
评论（3）
Pellet 和 Jess 主要可以用作语义推理器。然而，Jess 是一个基于规则的专家系统，用于为一些专家需要的问题提供答案。 Jess 也有自己的语言来创建规则。也就是说，我们称它们为杰斯规则。 Pellet 使用 Jena API 或 SWRL 来定义规则。因此，有了 Jess，您就可以编写更复杂的规则。如果你想在这些工具之间进行替换，你可能需要为每种类型重新编写一些规则。
在此链接中，您可以找到语义推理器之间的比较表。我以前没有使用过 SweetRules 推理器，但它似乎支持 SWRL 和 Jess 规则，因此这个推理器可以帮助在 Jess 和 Pellet 之间交叉。
Both Pellet and Jess can primarily be used as semantic reasoners. However Jess is a rule-based expert system which is used for providing answers to some expert needed problems. Also Jess has its own language to create rules. Namely we call them Jess Rules. Pellet uses Jena API or SWRL to define rules. So with Jess, you can write more complex rules. If you want to do a replacement between these tools, you may need to write some rules again for each type.
In this link you can find a comparison table between the semantic reasoners. I have not use SweetRules reasoner before but it seems that it supports both SWRL and Jess rules, therefore this reasoner can be helpfull in crossing between Jess and Pellet.
规则引擎可以将规则的定义与编码分开，并将推理过程放在规则引擎内部，这可以带来一些优势，例如重用规则知识。
Rule Engines can separate the definitions of rules apart from coding, and put the process of reasoning inner the rule engines, which could bring some advantages such as reusing the knowledge of rules.
推理机通常通过单调推理来实现更受限制的规则功能（如果有的话）。当人们说“reasoner”时，他们通常指的是 OWL 推理机，因为它是基于 RDF 的可互操作 W3C 推荐并且使用 公理和事实。
另一方面，诸如 CLIPS、Jess 或 Drools 之类的规则引擎具有完整的、独立的非标准编程语言，对可表达的内容几乎没有限制，并且不需要单独的功能部分 - 因此可能会导致缓慢且缓慢的结果。由于给予程序员的自由而导致系统设计不佳。
从技术上讲，可以使用任何规则引擎来代替推理器。作为一个具体的生产示例，可以将 Pellet 替换为 Drools 使用 Drools- SWRLAPI 用于 OWL/RDF 推理。 Jess 也有 SWRL API。然而，由于 Pellet 是一个内置 OWL 支持的专用推理器，它可以神奇地推断一切并通过 API 或 SPARQL 回答问题 - 而 Drools 需要特殊设置和大量编程来集成 Java API。
另一个现实世界的差异是规则引擎主要用作 BRMS（在 FinTech），而推理器则用于语义数据存储或知识管理应用程序，例如商品属性或关系新闻/媒体机构。
截至 2016 年，Pellet 的规则支持仅限于 SWRL，而 Drools-SWRLAPI 支持 SWRL 和 SQWRL（均为单调）。 SWRL 序列化本身是源自 Protege SWRLTab 插件的“事实上的”标准。
Reasoners usually implement a more constrained functionality of rules (if at all) with monotonic inference. When people say "reasoner" they generally mean OWL reasoner as it is an interoperable W3C recommendation based on RDF and may not have rule support at all with everything set up using Axioms and Facts.
Rule engines like CLIPS, Jess or Drools, on the other hand, feature a complete, self-contained non-standard programming language with little limitations on what can be expressed and with no need for a separate functional part - thus potentially leading to slow and poorly designed system due to freedom given to programmer.
Technically, any rule engine can be used instead of a reasoner. As a specific production example, one can replace Pellet with Drools using Drools-SWRLAPI for OWL/RDF reasoning. Jess also has SWRL API. However, as Pellet is a dedicated reasoner with built-in OWL support it magically infers everything and answers the questions via API or SPARQL - while Drools will require special setup and quite a bit of programming to integrate Java APIs.
Another real-world difference is that rule engines are primarily used as a BRMS (in FinTech for example) while reasoners are used in semantic data store or knowledge management applications like goods' properties or relationships in news/media agencies.
As of Y2016, rule support of Pellet is limited to SWRL and Drools-SWRLAPI supports both SWRL and SQWRL (both monotonic). SWRL serialization itself is a 'de-facto' standard derived from Protege SWRLTab plugin.