程序代写 ISBN 0387976892

Dr. Decision Systems Lab SCIT, EIS, UOW Ph.D. in Software Engineering M.Sc. in Computer Science B.Eng. in Computer Engineering

Decision Systems Lab
SCIT, EIS, UOW

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Ph.D. in Software Engineering
M.Sc. in Computer Science
B.Eng. in Computer Engineering

Engineering Human Values in Software through Value Programming (CHASE, 2020)

A Semantic Web Primer

Important Points about the Subject
A Semantic Web Primer

Please read the subject outline carefully!

Please discuss your technical questions in the lab!

Please email for what cannot be discussed in the lab!

The Semantic Web Vision &
Structured Web Documents in XML
Chapters 1 &2 of

Frank van Harmelen
A Semantic Web Primer

The Semantic Web Vision
https://www.w3.org/standards/semanticweb/

A Semantic Web Primer

Lecture Outline
Today’s Web
The Semantic Web Impact
Semantic Web Technologies
A Layered Approach

A Semantic Web Primer

What are the typical usages of the web?
A Semantic Web Primer

Today’s Web
Today’s web typical uses
seeking and making use of information,
searching for and getting in touch with other people,
reviewing catalogues of online stores ,
and ordering products by filling out forms

Most of today’s Web content is suitable for human consumption
Even Web content that is generated automatically from databases is usually presented without the original structural information found in databases

A Semantic Web Primer

Keyword-Based Search Engines
Current Web activities are not particularly well supported by software tools
Except for keyword-based search engines (e.g., Google)
The Web’s success relies on search engines.
A Semantic Web Primer

What are the problems with the current Keyword-Based Search Engines?
A Semantic Web Primer

A Semantic Web Primer

Results are highly sensitive to vocabulary
High recall but low precision
Low recall

Recall = tp/(tp+fn)
Precision = tp/(tp+fp)

Problems of Keyword-Based
Search Engines
https://medium.com/

Problems of Keyword-Based
Search Engines
Human involvement is necessary to interpret and combine results
Results of Web searches are not readily accessible by other software tools
A Semantic Web Primer

The Key Problem of Today’s Web
The meaning of Web content is not machine-accessible: lack of semantics
It is simply difficult to distinguish the meaning between these two sentences:
I am a lecturer of sematic web.
I am a lecturer of semantic web, you may think. Well, . . .
A Semantic Web Primer

Three key points with Semantic Web Approach:
Representing Web content in a form that is more easily machine-processable.
Using intelligent techniques to take advantage of these representations.
Evolving out of the existing Web
A Semantic Web Primer

Lecture Outline
Today’s Web
The Semantic Web Impact
Semantic Web Technologies
A Layered Approach
A Semantic Web Primer

The Semantic Web Impact – Knowledge Management
Knowledge management concerns with (i) acquiring, (ii) accessing, and (iii) maintaining knowledge within an organization
Key activity of large businesses: internal knowledge as an intellectual asset
Most information is currently available in a weakly structured form (e.g. text, audio, video)

A Semantic Web Primer

Limitations of Current Knowledge Management Technologies in four dimensions:
Searching information:
Keyword-based search engines
Extracting information:
human involvement necessary for browsing, retrieving, interpreting, combining
Maintaining information:
inconsistencies in terminology, outdated information.
Viewing information:
Impossible to define views on Web knowledge

A Semantic Web Primer

Semantic Web Enabled Knowledge Management
i) organizing knowledge in conceptual spaces according to its meaning.
ii) having automated tools for maintenance and knowledge discovery
iii) answering any query semantically
iv) answering any query over several documents
v) defining who may view certain parts of information (even parts of documents) will be possible.
A Semantic Web Primer

The Semantic Web Impact –
B2C Electronic Commmerce
A typical scenario: user visits one or several online shops, browses their offers, selects and orders products.
Ideally humans would visit all, or all major online stores; but time consuming
Shopbots are a useful tool:
https://www.shopbot.com.au/

A Semantic Web Primer

Limitations of Shopbots
They rely on wrappers: extensive programming required
Wrappers need to be reprogrammed when an online store changes its outfit
Wrappers extract information based on textual analysis
Error-prone
Limited information extracted

A Semantic Web Primer

Semantic Web Enabled B2C
Electronic Commerce
Software agents that can interpret the product information and the terms of service.
Pricing and product information, delivery and privacy policies will be interpreted and compared to the user requirements.
Information about the reputation of shops
Sophisticated shopping agents will be able to conduct automated negotiations

A Semantic Web Primer

The Semantic Web Impact –
B2B Electronic Commerce
Currently relies mostly on EDI (Electronic Data Interchange)
Isolated technology, understood only by experts
Difficult to program and maintain, error-prone
Each B2B communication requires separate programming
A Semantic Web Primer

Semantic Web Enabled B2B Electronic Commerce
(Advantages)
Businesses enter partnerships without much overhead
Differences in terminology will be resolved using standard abstract domain models
Data will be interchanged using translation services.
Auctioning, negotiations, and drafting contracts will be carried out automatically (or semi-automatically) by software agents
A Semantic Web Primer

Wikis are the next area Semantic Web can be useful:
Collections of web pages that allow users to add content via a browser interface
Wiki systems allow for collaborative knowledge
Users are free to add and change information without ownership of content, access restrictions, or rigid workflows
A Semantic Web Primer

Some Uses of Wikis
Development of bodies of knowledge in a community effort, with contributions from a wide range of users (e.g. Wikipedia)
Knowledge management of an activity or a project (e.g. brainstorming and exchanging ideas, coordinating activities, exchanging records of meetings)

A Semantic Web Primer

Semantic Web Enabled Wikis
The inherent structure of a wiki, given by the linking between pages, gets accessible to machines beyond mere navigation
Structured text and untyped hyperlinks are enriched by semantic annotations referring to an underlying model of the knowledge captured by the wiki
e.g. a hyperlink from Knossos to Heraklion could be annotated with information is located in. This information could then be used for context-specific presentations of pages, advanced querying, and consistency verification
A Semantic Web Primer

A Semantic Web Primer

Lecture Outline
Today’s Web
The Semantic Web Impact
Semantic Web Technologies
A Layered Approach
A Semantic Web Primer

Semantic Web Technologies
Explicit Metadata
Ontologies
Logic and Inference
A Semantic Web Primer

Web content is currently formatted for human readers rather than programs.
HTML is the predominant language in which Web pages are written (directly or using tools)
Vocabulary describes presentation
A Semantic Web Primer

An HTML Example

Agilitas Physiotherapy Centre

Welcome to the home page of the Agilitas Physiotherapy Centre. Do
you feel pain? Have you had an injury? Let our staff ,
(our lovely secretary) and take care
of your body and soul.

Consultation hours

Mon 11am – 7pm
Tue 11am – 7pm
Wed 3pm – 7pm
Thu 11am – 7pm
Fri 11am – 3pm

But note that we do not offer consultation during the weeks of the
State Of Origin games

A Semantic Web Primer

Problems with HTML
Humans have no problem with this
Machines (software agents) do:
How distinguish therapists from the secretary,
How determine exact consultation hours
They would have to follow the link to the State Of Origin games to find when they take place.
A Semantic Web Primer

A Better Representation
Physiotherapy Agilitas Physiotherapy Centre

A Semantic Web Primer

Explicit Metadata
This representation is far more easily processable by machines
Metadata: data about data
Metadata capture part of the meaning of data
Semantic Web does not rely on text-based manipulation, but rather on machine-processable metadata
A Semantic Web Primer

Ontologies
The term ontology originates from philosophy
The study of the nature of existence
Different meaning from computer science
An ontology is an explicit and formal specification of a conceptualization
A Semantic Web Primer

Typical Components of Ontologies
Terms denote important concepts (classes of objects) of the domain
e.g. professors, staff, students, courses, departments
Relationships between these terms: typically class hierarchies
a class C to be a subclass of another class C’ if every object in C is also included in C’
e.g. all professors are staff members

A Semantic Web Primer

Further Components of Ontologies
Properties:
e.g. X teaches Y
Value restrictions
e.g. only faculty members can teach courses
Disjointness statements
e.g. faculty and general staff are disjoint
Logical relationships between objects
e.g. every department must include at least 10 faculty members.

A Semantic Web Primer

Example of a Class Hierarchy

A Semantic Web Primer

The Role of Ontologies on the Web
Ontologies provide a shared understanding of a domain: semantic interoperability
overcome differences in terminology
mappings between ontologies
Ontologies are useful for the organization and navigation of Websites

A Semantic Web Primer

The Role of Ontologies in Web Search
Ontologies are useful for improving the accuracy of Web searches
search engines can look for pages that refer to a precise concept in an ontology
Web searches can exploit generalization/ specialization information
If a query fails to find any relevant documents, the search engine may suggest to the user a more general query.
If too many answers are retrieved, the search engine may suggest to the user some specializations.

A Semantic Web Primer

What is the difference between Ontology and Taxonomy?
A Semantic Web Primer

Web Ontology Languages
RDF (Resource Description Framework) Schema
RDF is a data model for objects and relations between them
RDF Schema is a vocabulary description language which
1) Describes properties and classes of RDF resources,
2) Provides semantics for generalization hierarchies of properties and classes

A Semantic Web Primer

Web Ontology Languages (2)
OWL (Web Ontology Language) OWL is built on top of RDF
A richer ontology language
relations between classes
e.g., disjointness
cardinality
e.g. “exactly one”
richer typing of properties
characteristics of properties (e.g., symmetry)
A Semantic Web Primer

Logic and Inference
Logic is the discipline that studies the principles of reasoning
Formal languages for expressing knowledge
Well-understood formal semantics
Declarative knowledge: we describe what holds without caring about how it can be deduced
Automated reasoners can deduce (infer) conclusions from the given knowledge
A Semantic Web Primer

An Inference Example
prof(X)  faculty(X)
faculty(X)  staff(X)
prof(michael)
We can deduce the following conclusions:
faculty(michael)
staff(michael)
prof(X)  staff(X)
A Semantic Web Primer

Logic versus Ontologies
The previous example involves knowledge typically found in ontologies
Logic can be used to uncover ontological knowledge that is implicitly given
It can also help uncover unexpected relationships and inconsistencies
Logic is more general than ontologies
It can also be used by intelligent agents for making decisions and selecting courses of action
A Semantic Web Primer

Tradeoff between Expressive Power and Computational Complexity
The more expressive a logic is, the more computationally expensive it becomes to draw conclusions
Drawing certain conclusions may become impossible if non-computability barriers are encountered.
Our previous examples involved rules “If conditions, then conclusion,” and only finitely many objects
This subset of logic is tractable and is supported by efficient reasoning tools
A Semantic Web Primer

Inference and Explanations
An important advantage of logic is that it can provide explanations for conclusions
Explanations: a series of inference steps that can be retraced
They increase users’ confidence in Semantic Web agents.
Activities between agents: create or validate proofs
A Semantic Web Primer

Typical Explanation Procedure
Facts will typically be traced to some Web addresses
The trust of the Web address will be verifiable by agents
Rules may be a part of a shared commerce ontology or the policy of the online shop
A Semantic Web Primer

Software Agents
Software agents work autonomously and proactively
They evolved out of object oriented and compontent-based programming
A Semantic Web Primer

Intelligent Personal Agents

A Semantic Web Primer

Semantic Web Agent Technologies
Identify and extract information from Web sources
Ontologies
Search websites and interpret retrieved information
Communicate with other agents
Process retrieved information, draw conclusions
A Semantic Web Primer

Semantic Web Agent Technologies (2)
Further technologies (orthogonal to the Semantic Web technologies)
Agent communication languages
Formal representation of beliefs, desires, and intentions of agents
Creation and maintenance of user models.
A Semantic Web Primer

What will a personal agent on the Semantic Web do? Name its operations one after another chronically (in a time-based sequence).
A Semantic Web Primer

A personal agent on the Semantic Web will:

receive some tasks and preferences from the person
seek information from Web sources, communicate with other agents
compare information about user requirements and preferences, make certain choices
give answers to the user

A Semantic Web Primer

Take a break!

Lecture Outline
Today’s Web
The Semantic Web Impact
Semantic Web Technologies
A Layered Approach
A Semantic Web Primer

The Semantic Web Layer Tower

A Semantic Web Primer
A General Semantic Web Layer Stack

A Specific Semantic Web Layer Stack
The main differences are:
The ontology layer is instantiated with two alternatives: the current standard Web ontology language, OWL, and a rule-based language
DLP (DataLog Logical Programming) is the intersection of OWL and Horn logic, and serves as a common foundation
The Semantic Web Architecture is currently being debated and may be subject to refinements and modifications in the future.
A Semantic Web Primer

A specific Semantic Web Layer Stack
A Semantic Web Primer

Semantic Web Layers
Syntactic basis
RDF basic data model for facts
RDF Schema simple ontology language
Ontology layer
More expressive languages than RDF Schema
Current Web standard: OWL

A Semantic Web Primer

Semantic Web Layers (2)
Logic layer
enhance ontology languages further
application-specific declarative knowledge
Proof layer
Proof generation, exchange, validation
Trust layer
Digital signatures
recommendations, rating agencies ….

A Semantic Web Primer

Chapter 2:
Structured Web Documents in XML
Introduction
Detailed Description of XML
Structuring
XML Schema
Namespaces
Accessing, querying XML documents: XPath
Transformations: XSLT
A Semantic Web Primer

A Semantic Web Primer

A Semantic Web Primer
An HTML Example

Nonmonotonic Reasoning: Context-
Dependent Reasoning

by V. Marek and
M. Truszczynski

Springer 1993
ISBN 0387976892

A Semantic Web Primer
The Same Example in XML
Nonmonotonic Reasoning: Context- Dependent Reasoning
V. Marek
M. Truszczynski Springer 1993
0387976892

A Semantic Web Primer
HTML versus XML: Similarities
Both use tags (e.g.

and )
Tags may be nested (tags within tags)
Human users can read and interpret both HTML and XML representations quite easily
… But how about machines?

A Semantic Web Primer
Problems with Automated Interpretation of HTML Documents
An intelligent agent trying to retrieve the names
of the authors of the book
Authors’ names could appear immediately after the title
or immediately after the word by
Are there two authors?
Or just one, called “V. Marek and M. Truszczynski”?

A Semantic Web Primer
HTML vs XML: Structural Information
HTML documents do not contain structural information: pieces of the document and their relationships.
XML more easily accessible to machines because
Every piece of information is described.
Relations are also defined through the nesting structure.
E.g., the tags appear within the tags, so they describe properties of the particular book.

A Semantic Web Primer
HTML vs XML: Structural Information (2)
A machine processing the XML document would be able to deduce that
the author element refers to the enclosing book element
XML allows the definition of constraints on values
E.g. a year must be a number of four digits

A Semantic Web Primer
HTML vs XML: Formatting
The HTML representation provides more than the XML representation:
The formatting of the document is also described
Τhe main use of an HTML document is to display information: it must define formatting
XML: separation of content from display
same information can be displayed in different ways

A Semantic Web Primer
HTML vs XML: Another Example

Relationship force-mass

F = M × a

Relationship force-mass
F
M × a

A Semantic Web Primer
HTML vs XML: Different Use of Tags

HTML tags define display: color, lists …
XML tags not fixed: user definable tags

Note that XML is a meta markup language: a language for defining markup languages

A Semantic Web Primer
XML Vocabularies
Web applications must agree on common vocabularies to communicate and collaborate
Communities and business sectors are defining their specialized vocabularies
mathematics (MathML)
bioinformatics (BSML)
human resources (HRML)

A Semantic Web Primer
Lecture Outline
Introduction
Detailed Description of XML
Structuring
XML Schema
Namespaces
Accessing, querying XML documents: XPath
Transformations: XSLT

A Semantic Web Primer
The XML Language

An XML document consists of:

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