1. China 20091 语义网的逻辑基础 Logical Foundation of the Semantic Web 主讲： 黄智生 Zhisheng Huang Vrije University Amsterdam ， The Netherlands huang@cs.vu.nl 助教： 胡伟 Wei Hu Southeast University whu@seu.edu.cn

2. China 20092 课程时间表 Schedule

3. China 20093 语义网的基本思想 RDF/RDFS OWL 语言 OWL-DL 及其与描述逻辑的关系 讲座 4 ：语义网与逻辑 Lecture 4: The Semantic Web and its Logics

4. China 20094 从 Google 谈起 starting from Google

5. China 20095 存在的问题 Existing Problems

6. China 20096 我们能不能做得更好？ Can we do it better? 基于语义的搜索 Semantics-based search 概念组合描述 concept combination specification 指定特定领域 domain specific 逼近搜索 approximate search 搜索代理 search agent

7. China 20097 语义网 (Semantic Web) 核心思想 : 给网络信息赋于确切定义的意义, 即语义。 „ The Semantic Web is an extension of the current web in which information is given well- defined meaning, better enabling computers and people to work in co-operation.“ [Berners-Lee et al., 2001]

8. China 20098 语义网想做什么？ (What the Semantic Web wants to do) 机器可自动处理 机器可理解 Content is machine-understandable if it is bound to some formal description of itself (i.e. metadata).

9. China 20099 万维网 : 影响和展望 WWW: Its impacts and visions

10. China 200910 网络 1.0 Web1.0

11. China 200911 网络 2.0 Web2.0

12. China 200912 对网络 3.0 的期待 Expectations on Web3.0 新颖性 (Novelty) ： 它不同于已有的 Web1.0 和 Web2.0 的技术，它能提供全新的一代网络服务 模式 ( 即为什么不是 Web1.0 或 Web2.0 ） 从字面上看对 Web3.0 的特征期待： 可行性 (Achievability) ：它在现有的网络环境下，经过努力是 可能实现的， 它并不存在不可逾越的技术障碍（即为什么不 是 Web4.0 或更高）。 迫切性 (Urgency) ：它提供网络服务是当前社会迫切需要的， 它的技术引入是能够对社会产生重大影响。（即为什么只能是 Web3.0 ）

13. China 200913 网络 3.0 Web3.0

14. China 200914 网络 1.0 – 网络 2.0 – 网络 3.0 Web1.0 – Web2.0 – Web3.0 网络 1.0 ： 文件网 Web1.0: Web of documents 网络 2.0 ： 人际 / 社会网 Web2.0: Web of persons 网络 3.0 ： 数据网 Web3.0: Web of data (semantics)

15. China 200915 网络发展整体观

16. China 200916 语义联接的好处：从一个实 例说起 Advantages of Linked Data

17. China 200917 数据联接的好处：小结 现有的网页是供人们阅读的，不便于机器自动处 理，数据联接便于机器自动处理 文件联接在局部文字上只允许一个链接，而数据 联接对局部文字支持多重链接 文件联接只提供部分文字链接，而数据联接保证 全文链接 基于关键词的搜索引擎如 Google 虽然看起来支持 全文检索，但它不能区分同一个词的不同含义， 这对于人名，地名等重复性频率较高的问题领域 处理尤其困难，而且在许多具体应用领域一词多 义的情形比比皆是。

18. China 200918 数据联接的统一概念格式 三元组 (Triple) 方法 : 例子： 提供网络资源的描述能力 例子： 提供语义的唯一标识 让数据内容独立于表达形式 提供初步的语义推理能力

19. China 200919 为什么推理支持是必要的？ 例子：从 ZhishengHuang 是自由大学的雇员 和自由大学在阿姆斯特丹，能够推出 ZhishengHuang 在阿姆斯特丹工作。,, - > = 》

20. China 200920 语义网与本体 Semantic Web and Ontologies

21. China 200921 五句话介绍语义网的主要思想： Why the Semantic Web ？ 任任何信息系统都需要数据； 数数据表示要独立于具体的应用和平台，以保证最大程度地可重 用； 采用统一的数据概念表示以保证数据表示独立于具体系统（即可 采用 Triple/Tuple 形式） ； 数数据应能描述网络资源（即要采用 RDF/RDFS 或其他类似的语 言） 数数据应提供初步的推理支持（即要采用 OWL 或其他知识表示语 言） （注意； RDF/RDFS/OWL 均采用 Triple 语义模型）

22. China 200922 发展趋势 根据美国著名市场研究公司 Gartner 的 2007 五月份报告， 到 2012 年， 70% 的 公开网页将带有一定程度的语义标注， 20% 将使用更强的基于语义网的本体。 Gartner (May 2007): "By 2012, 70% of public Web pages will have some level of semantic markup, 20% will use more extensive Semantic Web-based ontologies”

23. China 200923 海量语义数据的一部分 Ontologies and Metadata: Billion Triples dataset （十亿三元组数据集） 雅虎数据 东南大学数据 马里兰大学 英国 open 大学 SemWebBase （ DERI) 维基百科 地理名字 出版物 英文语义词典 Freebase 美国政府数据

24. China 200924 Linked Data 2009

25. China 200925 一个具体的数据联接的实例 http://sindice.com/apiv2/search?q=%22zhisheng%20huang %22&format=atom&page=1&qt=term

26. China 200926 一个具体的数据联接的实例 http://sindice.com/apiv2/search?q=%22zhisheng%20huang%22&f ormat=atom&page=5&qt=term

27. China 200927 Falcons

28. China 200928 让数据内容独立于表达形式

29. China 200929 More about the Semantic Web 请见 8 月 29 日 星期六的导课 09:00-12:00 导课 1 ： Introduction to the Semantic Web （ Ivan Herman ）

30. China 200930 HTML 标识 (HTML Markup) …… Zhisheng Huang Affiliation : Department of Computer Science Faculty of Sciences Vrije University Amsterdam Email : huang @ cs.vu.nl Phone : 31-20-4447740(office) ……

31. China 200931 XML 标注 XML-Annotations Zhisheng Huang Department of Computer Science Faculty of Sciences Vrije University Amsterdam huang @ cs.vu.nl (31)-20-4447740 ……

32. China 200932 Data Structures 结构化数据 Structured Data: Database 半结构化数据 Semi-structured Data: HTML, XML, BibTex 非结构化数据 Non-structured Data: Text

33. China 200933 关系数据库的 XML 表示 XML representation of a relational database John 1234567 Mary 7654321 ….. member idnamephone 001John1234567 002Mary7654321 ……… AI group

34. China 200934 文件类型定义 Document Type Definition(DTD) <!DOCTYPE researcher [ … ]>

35. China 200935 ResearcherAffiliation has Department Faculty University Name Phone eMail 1 n 数据模型 Data Model

36. China 200936 XML 模式 XML Schema The purpose of an XML Schema is to define the legal building blocks of an XML document, just like a DTD.

37. China 200937 Why XML Schemas XML Schemas are extensible to future additions XML Schemas are richer and more useful than DTDs XML Schemas are written in XML XML Schemas support data types XML Schemas support namespaces

38. China 200938 名字冲突 Name Conflicts Since element names in XML are not fixed, very often a name conflict will occur when two different documents use the same names describing two different types of elements. If these two XML documents were added together, there would be an element name conflict because both documents contain a same element with different content and definition.

39. China 200939 XML 名字空间 XML NameSpace Using Namespaces to solve Name Conflicts Examples: xmlns:namespace prefix="namespace" xmlns:xsd="http://www.w3.org/2001/XMLSche ma"

40. China 200940 可扩展标识语言模式 XML Schema <xsd:element name="affiliation" type="affil" minOccurs="1" maxOccurs="unbounded"/>

41. China 200941 资源描述框架 Resource Description Framework(RDF) Metadata is machine understandable information about web resources or anything that has an URI, it is represented as a set of independent assertions: http://wasp.cs.vu.nl/sekt/dig/dig.pdf Zhisheng Creator Cees Creator Triple: T(subject, attribute, values)

42. China 200942 RDF: Dublin Core The Dublin Core provides properties for describing network objects, suitable for use by network search engines. The Dublin Core is a set of predefined properties for describing documents. The first Dublin Core properties were defined at the Metadata Workshop in Dublin, Ohio in 1995 and is currently maintained by the Dublin Core Metadata Initiative.Dublin Core Metadata Initiative

43. China 200943 Dublin Core Metadata Initiative The Dublin Core Metadata Initiative is an open forum engaged in the development of interoperable online metadata standards that support a broad range of purposes and business models. http://dublincore.org/

44. China 200944 Annotating Metadata Guidance on expressing the Dublin Core within the Resource Description Framework (RDF) Eric Miller Paul Miller Dan Brickley Dublin Core; RDF; XML Dublin Core Metadata Initiative Dublin Core Data Model Working Group 1999-07-01 text/html en

45. China 200945 资源描述框架模式 RDF Schema (RDFS) RDFS defines vocabulary for RDF Organizes this vocabulary in a typed hierarchy Class, subClassOf, type Property, subPropertyOf domain, range

46. China 200946 RDFS Prof. Qu Hu ， W Person PhDStudentProfessor subClassOf type hasSuperVisor domain range type

47. China 200947 Using A Blank Node Here the blank node stands for the concept of "John Smith's address".

48. China 200948 Blank Node Identifiers Blank nodes must have a name for triple usage. Blank node identifiers have the form _:name exstaff:85740 exterms:address _:johnaddress. _:johnaddress exterms:street"1501 Grant Avenue". _:johnaddress exterms:city "Bedford". _:johnaddress exterms:state "Massachusetts". _:johnaddress exterms:zip"01730". If a node in a graph needs to be referenced from outside this context, a URIref is required. Blank nodes make binary relationships out of an n-ary one (between John and the street, city, etc.).

49. China 200949 资源描述框架模式 RDF Schema (RDFS) RDFS defines vocabulary for RDF Organizes this vocabulary in a typed hierarchy –Class, subClassOf, type –Property, subPropertyOf –domain, range

50. China 200950 4. Other RDF Capabilities Containers Collections Reification Structured Values

51. China 200951 本体的主要特征 Key features of an Ontology 特殊与一般关系 InstanceOf Relation (Instances) 部分与整体关系 PartOf Relation (property) 概念层次性 Concept hierarchy, – 概念包含关系 concept subsumption

52. China 200952 网络本体语言 Web Ontology Language (OWL) OWL is built on top of RDF OWL is for processing information on the web OWL was designed to be interpreted by computers OWL was not designed for being read by people OWL is written in XML OWL is a web standard

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56. China 200956 OWL Example: animals <rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:rdfs="http://www.w3.org/2000/01/rdf-schema#" xmlns:owl="http://www.w3.org/2002/07/owl#" xmlns:dc="http://purl.org/dc/elements/1.1/" xml:base="http://wasp.cs.vu.nl/sekt/ontology/animal">

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58. China 200958 DL for OWL: SHIQ SHIQ = ALCQHI R+

59. China 200959 SHOIN(D) and OWL-DL SHION(D): S: ALC + role transitivity H: role hiersrchies O: nominals I: Inverse roles N: cardinality restriction D: datatypes

60. China 200960 OWL2 (OWL1.1) New features OWL 2 adds new functionality with respect to OWL 1. Some of the new features are syntactic sugar (e.g., disjoint union of classes) while others offer new expressivity, including: keys; property chains; richer datatypes, data ranges; qualified cardinality restrictions; asymmetric, reflexive, and disjoint properties; and enhanced annotation capabilities

61. China 200961 OWL 变种的三个方向 (I) OWL 2 EL: 便于有效地对大规模本体 进行推理 OWL 2 EL enables polynomial time algorithms for all the standard reasoning tasks; it is particularly suitable for applications where very large ontologies are needed, and where expressive power can be traded for performance guarantees.

62. China 200962 OWL 变种的三个方向 (II) OWL 2 QL: 便于针对大规模数据进行基于 数据库技术的合取查询 OWL 2 QL enables conjunctive queries to be answered using standard relational database technology; suitable for applications where relatively lightweight ontologies are used to organize large numbers of individuals or where it is useful or necessary to access the data directly via relational queries (e.g., SQL)..

63. China 200963 合取查询 Conjunctive Queries Conjunctive queries are of the general form （ in the first order language ）

64. China 200964 OWL 变种的三个方向 (III) OWL 2 RL: 便于针对 RDF 数据进行规则扩 展的有效推理支持 OWL 2 RL enables the implementation of polynomial time reasoning algorithms using rule-extended database technologies operating directly on RDF triples; it is particularly suitable for applications where relatively lightweight ontologies are used to organize large numbers of individuals or where it is useful or necessary to operate directly on data in the form of RDF triples..

65. China 200965 OWL2 的三个变种

66. China 200966 More about OWL2 请见 8 月 28 日 星期五下午 特邀讲座（潘志霖博士 Jeff Z. Pan ）： OWL2

67. China 200967 More Notations F: role functionality Q: qualified cardinality restriction R: generalised role inclusion E: existential role restriction

68. China 200968 OWL Variants and DL OWL Full: is not a DL OWL DL: SHOIN(D) OWL Lite: SHIF(D) OWL2 Full: is not a DL OWL2 DL: SROIQ(D) OWL2 EL: EL++ OWL2 QL: DL-Lite OWL2 RL: DLP

69. China 200969 EL++ A lightweight description logic that admits sound and complete reasoning in polytime. Dropping the (allValusFrom) restriction, whereas (someValuesFrom) is retained. It should be noted, however, that EL++ does admit (objectPropertyRange), which can be seen as an important case of (allValuesFrom).

70. China 200970 EL++: Syntax and Semantics

71. China 200971 EL++ Ontologies SNOMED CT, the Systematized Nomenclature of Medizine, Clinical Terms. SNOMED is a large-scale commercial ontology that underlies the standardized terminology of the health-care systems in the US, the UK, and a couple of other countries. NCI. The Thesaurus of the National Cancer Institute. An ontology that formalizes terms related to cancer research. The Gene Ontology formalizes terms relating to genes and gene products. More than 95% of the axioms of the GALEN ontology can also be expressed in EL++.

72. China 200972 Description Logic Programs (DLP) Description Logic Programs is a Horn fragment of OWL 2. The distinguishing feature of DLP is that it is an existential-free fragment; that is, while reasoning, the universe is fixed in the sense that one only needs to consider the objects explicitly used in the facts of the ontology.

73. China 200973 Overview of DLP Features Essentially, DLP captures RDFS subset of DL - - plus a bit more. RDFS subset of DL permits the following statements: – Class C is Subclass of class D. – Domain of property P is class C. – Range restriction on property P is class D. – Property P is Subproperty of property Q. – a is an instance of class C. – (a,b) is an instance of property P.

74. China 200974 Overview of DLP Features(continued) DLP also captures: – Using the Intersection connective (conjunction) in class descriptions – Stating that a property P is Transitive. – Stating that a property P is Symmetric. DLP can partially capture: most other DL features. Relevant technical issues in LP: – treatment of equality, e.g., uniqueness of names.

75. China 200975 DLP and OWL DL DLP is able to express the following features of OWL DL: concept disjointness, domains and ranges of properties, inverse and symmetric properties, functional and inverse-functional properties, sub-property and equivalence relations between object properties, transitive properties, and a limited form of General Concept Inclusion axioms (GCIs).

76. China 200976 DL-Lite DL-Lite is a fragment of OWL DL especially tailored for handling efficiently large number of facts. The main focus is to provide efficient query answering on the data and to allow the use of Relational Database Managment technologies for such a purpose.

77. China 200977 DL-Lite DL-Lite also includes most of the main features of conceptual models, like UML class diagrams and ER diagrams. More specifically, DL-Lite includes the following features of OWL DL: a constrained form of someValuesFrom restrictions, conjunction, concept disjointness, domains and ranges of properties, inverse properties, inclusion axioms for object properties.

78. China 200978 Complexity The Data Complexity: the complexity measured with respect to the number of facts in the ontology. The Taxonomic complexity: the complexity measured with respect to the size of the axioms in the ontology. The Query Complexity: the complexity measured with respect to the number of conjuncts in the conjunctive query. The Combined Complexity: the complexity measured with respect to both the size of the axioms and the number of facts. In the case of conjunctive query answering, the combined complexity also includes the query complexity.

79. China 200979 Complexity of Tractable Fragments- OWL DL

80. China 200980 Complexity of Tractable Fragments- OWL Lite

81. China 200981 Complexity of Tractable Fragments- EL++

82. China 200982 Complexity of Tractable Fragments- DL-Lite

83. China 200983 Complexity of Tractable Fragments- DLP

84. China 200984 Relationship between the fragments of OWL1.1(OWL2)

85. China 200985 Key Issues of the Semantic Web 数据，知识与语义 data ， knowledge ， and semantics 语义相关性， 语义相似性，与语义距离 Semantic relevance, semantic similarity, and semantic distance 知识表示与推理 Knowledge representation and reasoning 海量语义数据处理 Scalability 近似推理 Approximate reasoning

86. China 200986 语义网应用的一些实例： DBpedia Mobile http://beckr.org/DBpediaMobile/?location= Beijinghttp://beckr.org/DBpediaMobile/?location= Beijing http://beckr.org/DBpediaMobile

87. China 200987 芬兰医疗语义网 HealthFinland – Health Information on the Semantic Web http://www.seco.tkk.fi/applications/tervesu omi/ provide a new kind of solution approach to these problems on a national Finnish level. The system consists of three main components: Metadata, ontology, and service infrastructure. Semantic content creation process. A content creation and harvesting system has been implemented for producing semantically annotated contents, based on the shared metadata model and ontologies. Semantic portal HealthFinland (TerveSuomi) and its services. The material is published via a semantic portal that creates a single national entry-point for health information, health promotion and health-related news.

88. China 200988 National Semantic Web Ontology Project in Finland (FinnONTO), National Semantic Web Ontology Project in Finland (FinnONTO), 2003-2007 A large national continuation project of FinnONTO, called Semantic Web 2.0 (FinnONTO 2.0), started in the beginning of 2008.Semantic Web 2.0 (FinnONTO 2.0) The research is directed and is mostly carried our by the Semantic Computing Research Group (SeCo) at the Helsinki University of Technology (TKK) and the University of Helsinki. Also the University of Tampere is contributing to the work. The consortium behind the project included 37 public organizations and companies funding the research during the final year 2007. This consortium represents a wide area of functions of the society including museums, libraries, business, health organizations, government, media, and education. Public organizations, companies, and universities are participating in the project.

89. China 200989 荷兰国家文化传承工程 The Dutch Cultural Heritage  Eculture Project  STiTCH-Catch  Chip Project

90. China 200990 Project E-Culture http://e-culture.multimedian.nl/

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96. China 200996 2006 国际语义网技术挑战赛冠军

97. China 200997 http://www.ontology-advisory.org/

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100. China 2009100 Balkenende attacks Bos “You’re a twister and dishonest”, said the Christian Democrat about his most main opponent (30/10/06) Polls: SP at 25 seats larger than VVD According to a poll conducted by TNS/NIPO, the SP has risen to be the third largest party. (7/11/06) Unrest in VVD over Rutte Liberal MP’s also complain about personal campaign by Rita Verdonk. (1/11/2006) Reality + SP Reality - VVD Balkenende – Bos Balkenende: Bos - Ideal VVD – VVD VVD – Verdonk 语义网应用于政治分析 实例研究： 2006 年荷兰大选

101. China 2009101 Relational Content Analysis

102. China 2009102 Example

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104. China 2009104 趋势分析与预测

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106. China 2009106 时间推理

107. China 2009107 逻辑的作用 使用混合逻辑（ Hybrid Logic ）与事态 逻辑描述性质：如 Internal Disagrement 等

108. China 2009108 练习题 用 OWL-DL 来描述家族本体 罗列一些无法用 OWL-DL 描述的 本体性质，并提出一些变通的表 达方案 研究 OWL-DL 的合取查询的可判 断性与复杂性

109. China 2009109 语义网逻辑基础演义 第五回：信息浩瀚语义万维网横空出世 语义搜索本体技术域众人瞩目 欲知后事如何，请听下回分解。。。

110. China 2009110 Questions and Discussions