Semantic Web Based on The semantic web Ontologies

Semantic Web Based on: -The semantic web -Ontologies Come of Age Clément Troprès - Damien Coppéré 1

Plan l Introduction to semantic web l Kwnoledge Representation l Ontologies l Agents Clément Troprès - Damien Coppéré 2

1. Introduction to semantic web l Today, most of the web contents is designed for human to read l The actual web looks insufficient l The semantic web purpose is to structure the world wide web Clément Troprès - Damien Coppéré 3

1. Introduction to semantic web l Principles: 1. Each object of the web has a metadata Each metadata is readable by agents and humans Each metadata represents accurately an object 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 2. 3. 4. Clément Troprès - Damien Coppéré 4

1. Introduction to semantic web The semantic web architecture Clément Troprès - Damien Coppéré 5

2. Knowledge representation (1): l Technology which permits computers to access to structured collections of information l System must have sets of inference rules that computers can use to conduct automated reasoning l It has to be linked into a single global system Clément Troprès - Damien Coppéré 6

2. Knowledge representation (2) : l Traditional systems usually : - Limit the questions that can be asked - Become unmanageable l New systems, in contrast, accept paradoxes - Unanswerable questions are a price that must be paid to achieve versatility. Clément Troprès - Damien Coppéré 7

2. Knowledge representation (3) : l Two important technologies exist : - EXtensible Markup Language (XML) - Resource Description Framework (RDF) l XML : - Everyone can create their own tags - It allows to add arbitrary structure to the document Clément Troprès - Damien Coppéré 8

2. Knowledge representation (4) : l 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%20 York"> <"http: //purl. org/dc/terms/" : alternative>NY</rdf: Description> l Universal Resource Identifier - Ensure that concepts are tied to a unique definition that everyone can find on the Web Clément Troprès - Damien Coppéré 9

3. Ontologies - Introduction l Current web : It has grown and continues to grow very quickly Problems to find information you are really looking for Designed for human perception l Semantic web: Make the web understandable by computers agent Clément Troprès - Damien Coppéré 10

3. Ontologies - Introduction l 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 Clément Troprès - Damien Coppéré 11

3. Ontologies - Introduction We are here Clément Troprès - Damien Coppéré 12

3. Ontologies - Introduction l Definition: - In 1993, Gruber propose his definition (which is now the most cited in AI) : « An ontology is an explicit specification of a conceptualization » . (Gruber T. , 1993 b) - In 1997, Borst modified slightly the definition in order to highlight major aspects of this paradigm: « An ontology is a formal specification of a shared conceptualization » . (Borst W. N. , 1997) Clément Troprès - Damien Coppéré 13

3. Ontologies - Introduction l 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 Clément Troprès - Damien Coppéré 14

3. Ontologies - Introduction l « Formal » means that ontology is interpretable by a machine (machinereadable) l « explicit specification » means that the concepts of ontology and the constraints related to their use are defined in a declaratory way l Ontology has the following characteristics : 1) shared, 2) explicit, 3) formal Clément Troprès - Damien Coppéré 15

3. Ontologies – Possible representation? l l l l A controlled vocabulary (eg: Catalogs) A glossary (list of terms) Thesauri (synonym relationship…, but not an explicit hierarchy) A Term hierarchies (without true subclass) Strict subclass hierarchies A is a superclass of B Frames (classes include property information) B Value restriction (eg: a price is a number) Logical deduction Clément Troprès - Damien Coppéré 16

3. Ontologies – Simple Ontologies l 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 - Clément Troprès - Damien Coppéré 17

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 Clément Troprès - Damien Coppéré 18

3. Ontologies – Implications and Needs l An ontology-based application has two major concerns: The language The environment Clément Troprès - Damien Coppéré 19

3. Ontologies – Implications and Needs (1) l 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) Clément Troprès - Damien Coppéré 20

3. Ontologies – Implications and Needs (2) l Environment: Ontology tools are needed to analyze, modify and maintain an ontology over time Many are avalaible commercially Clément Troprès - Damien Coppéré 21

3. Ontologies – Implications and Needs (3) l 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) Clément Troprès - Damien Coppéré 22

3. Ontologies – Implications and Needs (4) l 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) Clément Troprès - Damien Coppéré 23

4. Agents l Representing by programs : - Collect Web content from diverse sources - Process the information - Exchange the results with other programs l All agents can work together Clément Troprès - Damien Coppéré 24

4. Agents (2) l 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 l Example of agent : You answer your phone and the stereo sound which was working is turned down. Clément Troprès - Damien Coppéré 25

4. Agents (3) l 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…) l Travel Agency… Clément Troprès - Damien Coppéré 26

The Semantic Web - Lets anyone express new concepts with minimal effort - Unifies a logical language Clément Troprès - Damien Coppéré 27