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所在平台: Udemy |
课程主页: https://www.udemy.com/course/introduction-the-semantic-web-with-python/
课程评论：没有评论
**课程名称：** 语义网入门与Python实践 **课程概述：** 本课程将深入介绍语义网的核心概念，并结合Python这一流行编程语言进行实践。课程首先会阐述语义网的重要性和数据整合的必要性，探讨Web的架构，并分析表格数据和关系数据等传统数据模型。接着，课程将逐步演进和重构数据模式，展示如何通过实例增加数据的灵活性。此外，还将讲解语义关系、元数据即数据的重要性，以及“为意料之外而构建”和“永久Beta”等理念。 课程的第二部分将进行实践操作：使用Python创建三元组库（Triplestore），实现数据的添加、删除和查询，并演示图的合并。更进一步，课程将介绍前馈推理（feed-forward inference）、规则链实现、基础图可视化等进阶主题。 最后，课程将引入一些未来可深入探索的概念和工具，如RDF数据模型、RDF序列化格式（RDL/XML, RDFa, RDFLib）以及SPARQL查询语言。
In this course we will teach you the most important concepts regarding Semantic Web and you will have the opportunity to practice them in a popular programming language (Python). First we will introduct you into the Semantic Web World with a crutial motivation. We gonna see how important is the data integration accross the web. We gonna see the web architecture. We will analize some traditional data models like tabular data and relational data. Next we will evolve and refactor the schemas presented. We will present how to add flexibility to our data with some examples to show how the concepts are useful. We gonna see Semantic Relationships, also that Metadata is Data, the importance to build for the Unexpected and Perpetual Beta. Last but not least we will show the examples in practice on a hands on approach in second section.We will create our Triplestore in Python and manage how to add, remove and query over it.We also gonna implement the merging graphs. In a more advanced moment we gonna show feed-forward inference, implement chains of rules, see some basic graph visualization.To finish we will introduce some concepts and tools that can be explored in a future course: RDF Data Model, RDF Serialization Formats, RDL/XML, RDFa, RDFLib and SPARQL.
