Clément Troprès - Damien Coppéré1 Semantic Web Based on: -The semantic web -Ontologies Come of...

Clément Troprès - Damien Coppéré 1

Semantic Web

Based on:

-The semantic web

-Ontologies Come of Age


Plan

Introduction to semantic web

Kwnoledge Representation

Ontologies

Agents


1. Introduction to semantic web

Today, most of the web contents is designed for human to read

The actual web looks insufficient

The semantic web purpose is to structure the world wide web


1. Introduction to semantic web

Principles:

1. Each object of the web has a metadata

2. Each metadata is readable by agents and humans

3. Each metadata represents accurately an object

4. Each metadata is available in a common space, readable by agents and humans. The selection of the metadata makes the object avalaible as a resource


1. Introduction to semantic webThe semantic web architecture


2. Knowledge representation (1):

Technology which permits computers to access to structured collections of information

System must have sets of inference rules that computers can use to conduct automated reasoning

It has to be linked into a single global system


2. Knowledge representation (2) :

Traditional systems usually :

- Limit the questions that can be asked

- Become unmanageable

New systems, in contrast, accept paradoxes

- Unanswerable questions are a price that must be paid to achieve versatility.


2. Knowledge representation (3) :

Two important technologies exist :

- EXtensible Markup Language (XML)

- Resource Description Framework (RDF)

XML :

- Everyone can create their own tags

- It allows to add arbitrary structure to the document


2. Knowledge representation (4) : RDF :

- Encode in sets of triplets - Each triple being rather like the subject, predicate and object of an elementary sentence identified by URIs - Natural way to describe the vast majority of the data processed by machines - Example : New York has a postal abbreviation which is NY

<rdf:Description rdf:about="urn:states:New%20York"> <"http://purl.org/dc/terms/" :alternative>NY</rdf:Description>

Universal Resource Identifier - Ensure that concepts are tied to a unique definition that

everyone can find on the Web


3. Ontologies - Introduction

Current web :

It has grown and continues to grow very quickly

Problems to find information you are really looking for

Designed for human perception

Semantic web:Make the web understandable by computers agent



How make the web semantic?

- Complete HTML tag (with XML)

- Organize the keywords in each document

- Indexing all the resources of the web (RDF)

- Ontologies



We arehere



Definition:- In 1993, Gruber propose his definition (which is now the most cited in AI) :

« An ontology is an explicit specification of aconceptualization ». (Gruber T., 1993b)

- In 1997, Borst modified slightly the definition in order to highlight major aspects of this paradigm:

« An ontology is a formal specification of a sharedconceptualization ». (Borst W. N., 1997)



Definition:In 1998, these two definitions were only one in the definition of Studer.

« An ontology is a formal, explicit specification of a shared conceptualization ». (Studer R. et al., 1998)

- « Conceptualization » refers to an abstraction of a phenomenon obtained by identifying the concepts appropriate to this phenomenon - « Shared » means that ontology captures consensual knowledge


3. Ontologies - Introduction « Formal » means that ontology is interpretable by a

machine (machinereadable)

« explicit specification » means that the concepts of ontology and the constraints related to their use are defined in a declaratory way

Ontology has the following characteristics :

1) shared, 2) explicit, 3) formal


3.Ontologies – Possible representation?

A controlled vocabulary (eg: Catalogs) A glossary (list of terms) Thesauri (synonym relationship…, but not an explicit

hierarchy) Term hierarchies (without true subclass) Strict subclass hierarchies Frames (classes include property information) Value restriction (eg: a price is a number) Logical deduction

A

B

A is a superclass of B


3. Ontologies – Simple Ontologies

Some of the ways that simple ontologies may be used in practice:

- A controlled vocabulary (beginning of interoperability)- Site organization and navigation support- Expectation setting- Umbrella structures from which to extend content- Browsing support- Search support- Sense disambiguation support


3. Ontologies – Structural Ontologies

- Consistency checking- Completion- Interoperability support- Support validation and verification testing- Encode entire test suites- Configuration support- Support structured, comparative and customized search- Exploit generalization/specialization information


3. Ontologies – Implications and Needs

An ontology-based application has two major concerns:

The language

The environment


3. Ontologies – Implications and Needs (1)

The language:

Simple ontologie: It’s not a real problem (language with subclass and instance relationships)

Structural ontologie: the language must be able to express the entire domain unambiguously (KRSS, KIF, OKBC)



Environment:

Ontology tools are needed to analyze, modify and maintain an ontology over time

Many are avalaible commercially



Environment – Criterias needed :

- Collaboration and distributed workforce support (share session)

- Platform interconnectivity (able to read and write compatible formats)

- Scale (In terms of size of ontologies, number of simultaneous users)

- Versioning (Able to support many versions of ontology)



Environment – Major criteria of performance :

- Security

- Analysis (focus the user’s attention in areas which need modification)

- Lifecyle issues (Support for ontology evolution issues)

- Ease of use (training materials, tutorials…)

- Diverse user support

- Presentation style

- Extensibility (Adapt along with the needs)


4. Agents

Representing by programs :

- Collect Web content from diverse sources

- Process the information

- Exchange the results with other programs

All agents can work together


4. Agents (2)

Important facets :

- "Proofs" written in the Semantic Web's unifying language (Proof Markup Language PML)

- Digital signatures used to verify that the attached information has been provided by a specific trusted source

Example of agent : You answer your phone and the

stereo sound which was working is turned down.


4. Agents (3) You want to buy a car …

An intelligent Agent is going to find your new car- How ? It looks for all cars which corespond to your criterias- Which criteria ?Prices, delivery period, colour… - Where ? On web documents described by semantic standards (proofs, digital signature…)

Travel Agency…


- Lets anyone express new concepts with minimal effort

- Unifies a logical language

The Semantic Web

Clément Troprès - Damien Coppéré1 Semantic Web Based on: -The semantic web -Ontologies Come of...

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