The Semantic Web has the goal of creating Web infrastructure that augments data with metadata to give it meaning, thus making it suitable for automation, integration, reasoning, and re-use.
语义web的目标是创建Web基础设施，使用元数据对数据进行增强，从而使数据变得有意义，最终使数据变得适合进行自动化、集成、推理和重用。
Near the top of the Semantic Web stack one finds inference - reasoning over data through rules.
在语义网络的接近顶层，人们可以发现推理—通过规则的对数据的推理。
This paper presents semantic reasoning based on UDDI Web Service registry model and this method is applied in E-Business Credit evaluating services.
论文在对UD鄄DI服务发现基本模型的研究基础上加入了语义推理，并运用到电子商务信用评估服务发现中。
The key reasoning tasks of the semantic Web can be reduced to deciding the satisfiability of formulas.
语义网的关键推理问题可以化为公式的可满足性判定问题。
Cell Cycle Ontology is enabled by semantic web technologies, and is accessible via the web for browsing, visualizing, advanced querying, and computational reasoning.
细胞周期本体论通过语义网技术成为可能，并可以通过网络访问用于浏览、可视化、高级查询及计算推理。
Semantic Web; Ontology; Adaptive Learning; Learner Model; Knowledge Management; Intelligent Reasoning; Cognitive Ability; Constructivism; Semantic Distance; Semantic Similarity.
语义网；本体；自适应学习；学习者模型；知识管理；智能推理；认知能力；建构主义； 语义距离； 语义相似度。
Semantic Web; Ontology; Adaptive Learning; Learner Model; Knowledge Management; Intelligent Reasoning; Cognitive Ability; Constructivism; Semantic Distance; Semantic Similarity.
语义网；本体；自适应学习；学习者模型；知识管理；智能推理；认知能力；建构主义； 语义距离； 语义相似度。
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