Knowledge Engineering with Semantic Web Technologies

The knowledge contained in the World Wide Web is available in interlinked documents written in natural language. To make use of this knowledge, technologies such as natural language processing, information retrieval, data and knowledge mining must be applied. Semantic Web technologies follow an alternative approach by complementing web documents with explicit semantics based on formal knowledge representations, such as e.g. ontologies. In this MOOC, you will learn the fundamentals of Semantic Web technologies and how they are applied for knowledge representation in the World Wide Web. You will learn how to represent knowledge with ontologies and how to access and benefit from semantic data on the Web. Furthermore, you will also learn how to make use of Linked Data and the Web of Data, currently the most popular applications based on Semantic Web technologies.

自一月 2, 2016起开始自学
语言: English
Big Data and AI, Expert, Internet

课程信息

The web has become an object of our daily life and the amount of information in the web is ever growing. Besides plain texts, especially multimedia information such as graphics, audio or video have become a predominant part of the web's information traffic. But, how can we find useful information within this huge information space? How can we make use of the knowledge contained in those web documents? Traditional search engines for example will reach the limits of their power, when it comes to understanding information content. The Semantic Web is an extension of the traditional web in the sense that information in the form of natural language text in the web will be complemented by its explicit semantics based on a formal knowledge representation. Thus, the meaning of information expressed in natural language can be accessed in an automated way and interpreted correctly, i.e. it can be ‘understood’ by machines.

Semantic Web technologies enable the explicit representation of knowledge and its further processing to deduce new knowledge from implicitly hidden knowledge. Thus, information access and information search will be more precise and more complete compared to today's traditional information retrieval technology. Previously heterogeneous data can be mapped and combined based on common knowledge representation and schemata easily extended in a dynamic way.

In this MOOC, you will learn the fundamentals of Semantic Web technologies and how they are applied for knowledge representation in the World Wide Web. You will learn how to represent knowledge with ontologies and how to access and benefit from semantic data on the Web. Furthermore, you will also learn how to make use of Linked Data and the Web of Data, currently the most popular applications based on Semantic Web technologies.

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This year's course differs from the 2014 edition in the following way:

  • more emphasis on knowledge engineering with practical examples

  • there are many EXTRA parts at the end of each lecture week covering additional and in depth topics. These parts marked with EXTRA are NOT GRADED and also not subject of the exams. They are not an 'official' part of the course, but only a voluntary addendum to deepen your knowledge.

Requirements for this course:

  • a basic knowledge of the foundations of mathematical logics, i.e. propositional logics and first order logics

  • a basic understanding of web technologies, such as URL, http, HTML, and XML-based technologies

  • a basic knowledge of database technology such as, e.g. relational databases and SQL query language

课程内容

  • Week 1:

    Knowledge Engineering and the Web of Data
  • Week 2:

    RDF Based Knowledge Engineering
  • Week 3:

    Ontologies and Logic
  • Week 4:

    OWL, Rules, and Reasoning
  • Week 5:

    Ontological Engineering
  • Week 6:

    Knowledge Engineering
  • Final Examination

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该课程提供者

Prof. Dr. Harald Sack

哈拉尔德-萨克是卡尔斯鲁厄FIZ-莱布尼茨信息基础设施研究所和卡尔斯鲁厄技术研究所的信息服务工程教授。1990年在联邦部队慕尼黑校区大学计算机科学专业毕业后,1990-1997年他在德国联邦部队的信号情报团担任系统/网络工程师和项目经理。1997年,他成为特里尔大学 "数学优化 "研究生项目的联系成员,并于2002年获得计算机科学博士学位。2002-2009年在耶拿的弗里德里希-席勒大学担任博士后。2009-2016年,他在波茨坦大学哈索-普拉特纳信息技术-系统工程研究所(HPI)担任高级研究员和 "语义技术 "研究组组长。

他的研究领域包括语义技术、知识图谱和知识表示、本体工程、知识提取、机器学习、语义和探索性搜索。

他是2008年成立的德国IPv6委员会的特许成员和秘书长。他曾在许多与语义技术有关的国际会议和研讨会中担任高级计算机成员或计算机成员,并担任项目主席、科学主席或总主席。

Harald Sack在国际期刊和会议上发表了200多篇论文,包括三本网络技术的标准教科书。他是yovisto GmbH(www.yovisto.com)的共同创始人。

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