of 33 lecture 1: introduction. of 33 the semantic web vision today’s web (1) web content – for...

of 33

lecture 1: introduction

of 33

the semantic web visiontoday’s web (1)

web content – for human consumption (no structural information)

people search for information, keep in touch with other people, make purchases, look for entertainment … minimal support by software tools

ece 720, winter'12 2

of 33


keyword-based search engines … with some problems:

high recall & low precision – too many documents retrieved

low/no recall – no relevant documents found results sensitive to vocabulary – similar words not considered

results are single web pages – “distributed” information not retrieved

human needed for interpretation, no other software tools use the result


of 33


a problem with semantics …so… a need for different representation of information, and intelligence that takes advantage of that


of 33

the semantic web vision… the future (1)

knowledge management key activity of large businesses (knowledge seen as intellectual asset)

information is in a weakly structured form

problems with: sharing, extracting, marinating, viewing

Semantic Web -> knowledge organized, tools for knowledge maintenance, query answering tools


of 33


business-to-customer electronic commerce browsing on-line shops, selecting the best alternative/offer -> time and effort consuming activity

decisions making based on limited/partial information

Semantic Web -> software “shopping” agents able to interpret the product information and the terms of service, and conduct negotiations


of 33


business-to-business electronic commerce data exchange using the Electronic Data Interchange (EDI) approach (complex, isolated)

lack of standards

Semantic Web -> differences in terminology resolved (abstract domain models), automatic translation of services, auctioning, negotiations, and drafting of contracts


of 33


wikis collections of pages that allow users to add content (collaborative knowledge creation)

Semantic Web -> usage of semantic technologies (enriching structured text and untyped hyperlinks with semantic annotation referring to an underlying model of the captured knowledge)


of 33


personal agents: a future scenario

Michael has some neck pain, he asked his Semantic Web agent to arrange for him physical therapy sessions which were suggested by Michael’s physician …


of 33

semantic web technologiesmetadata (1)

HTML is the predominant language used for writing web pages

humans have no problem reading itmachines are not able to distinguish different people, things, follow links to find out more about topics – simple they have no clue what a given text is about


of 33


<company> <companyName>… </companyName><staff>

<director> … </director><viceDirector> …

</viceDirector></staff>

</company>


of 33


HTML is replaced by a language that carries information about a contentmetadata – data about data, capture part of the meaning of data (tags that are “defined” in a systematic way)


of 33

semantic web technologiesontology (1)study of nature of existence, how to describe things that actually existworld is made up of specific objects that can be grouped into abstract classes based on shared propertiesit describes a domain of interest


of 33

semantic web technologiesontology (2)consists of a finite list of terms and the relationships between themterms denote concepts (classes of objects) of the domainrelationships include hierarchies of classes + properties of objects, value restrictions, logical relationships between objects


of 33

semantic web technologiesontology (3)

provide “a shared understanding of a domain”overcome differences in terminology


of 33

semantic web technologiesontology languagesRDF – is a data model for objects and relations between themRDF Schema – a description language for describing properties and classes of RDF resources, provides a semantics for generalization hierarchiesOWL – a rich language for describing properties and classes, and relations between them


of 33

semantic web versus AIlogic (1)provides principles of reasoningprovides well-understood formal semantics“unlocks” automated reasoners

leads to uncovering ontological knowledge given implicitly


of 33

semantic web versus AIlogic (2)

used by intelligent agents for making decisions and selecting courses of action

provides explanations for conclusions


of 33

semantic web versus AIlogic (3)

SWRL – semantic web rule language for constructing rules based on ontology classes and relationships


of 33

semantic web versus AIagents (1)

software agents work autonomously and proactively


of 33

semantic web versus AIagents (2)tasks of personal software agent in SW: receive tasks and preferences from users seek information on the web, communicate with other agents

compare information from different sources, make choices

give answer to users


of 33

semantic web versus AIagents (3)metadata identify and extract information

ontology web search, information interpretation communication with other agents

logic information retrieval, conclusion derivation


of 33

a layered approach

development of SW in steps

each step building a layer on the top of another


of 33

a layered approach


of 33

a layered approach


alternative stack

of 33

a layered approachXML layer syntactic basis

RDF layer basic data model for facts RDF Schema simple ontology language

ontology layer more expressive languages - OWL


of 33

a layered approachlogic layer enhance ontology, application specific knowledge

proof layer proof generation, validation

trust layer digital signature, rating agents …


of 33

the semantic web vision… the present (1)

linked data

a new paradigm built on one of the layers of SW – RDF core


of 33


linked data

each piece of information is linked to other pieces

different types of linksdifferent sources of data


of 33


linked data

every piece of information presented as a triple:subject-property-object


of 33


linked data

a vast, interconnected web of triples (pieces of information)easy to query with SPARQL – a special query language for RDF


of 33

the semantic web vision… linked data

linked data


of 33

future web …

intelligent representationand processing of data


of 33 lecture 1: introduction. of 33 the semantic web vision today’s web (1) web content – for...

Documents