Institut für Wissenstechnologien

1

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Introduction toSemantic Technologies

Viktoria Pammer-Schindler, Wolfgang Kienreich

October 11, 2012

Institut für Wissenstechnologien

2

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Syntax versus Semantics

Syntax

Greek συνταξις – arrangement, ordering

„The study of the principles and processes by which sentences are constructed in particular languages“ [Chomsky 1957]

Semantics

(grch. σημαντικος – about characters

“The study of interpretation of signs or symbols as used (…) within particular contexts” [Neurath et al. 1995]

Institut für Wissenstechnologien

3

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Do you pme#?

Symbols

p,m,e,#

Rules

A sequence of # starts and ends every sentence

Each out of p,m,e is always preceeded by a sequence of #

Each out of p,m,e is always followed by a sequence of #

The e is always the last out of p,m,e to be used

The e is always used exactly once

#p#e#, ###m#p#e##, ##p#e#, #m#m#m#p##p##e###

p#p#e#, #p##e, ###

Institut für Wissenstechnologien

4

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantics of pme#

#p#e##

#p##m#e##

###m##e#

#p##e#

##m##e####

###m##e#####

Institut für Wissenstechnologien

5

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Another interpretation of pme#

#p#m#e##

##m##e####

###m##e######

#m#e##

#p##m#e##

###m##e#

Institut für Wissenstechnologien

6

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

contextualized information applicable for problem solving

„an ontology is a formal, explicit specification of a shared conceptualisation”

„knowledge is information in (contextualized) action (application)”

Semantics and Knowledge

[Gruber 1993]

[Kuhlen 1995]

[Kienreich 2012]

Institut für Wissenstechnologien

7

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic TechnologiesTechnologies for working with

contextualized information (knowledge?)

A priori

Explicitly model knowledge

A posteriori

Extract implicit knowledge

Institut für Wissenstechnologien

8

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic TechnologiesA Posteriori Peak

▼A Priori Summit

▼Mount NLP

▼

Machine Learning Ridge

▼Point

Statistic

▼

Analytical Cliff

▼

Knowledge Base

▼

First Order Ridge

▼Second Order Valley

▼Ontology hills

▼

Data Flow

▼

Institut für Wissenstechnologien

9

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic TechnologiesA Posteriori Peak

▼A Priori Summit

▼Mount NLP

▼

Machine Learning Ridge

▼Point

Statistic

▼

Analytical Cliff

▼

Knowledge Base

▼

First Order Ridge

▼Second Order Valley

▼Ontology hills

▼

Data Flow

▼

Institut für Wissenstechnologien

10

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Chris Welty on Semantic Technologies as Bridge

Download video

Institut für Wissenstechnologien

11

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic Technologies

Working with contextualized information (knowledge?)

Common understanding: Semantic Technologies are about about encoding meaning and working with it

But there is more:

Semantic Search

Semantic Web

Semantic Mediation

…

Many areas (search…) are saturated with standard (statistical, non context-aware) methods. New, semantic methods are required for the next step

Institut für Wissenstechnologien

12

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic Technologies

Example: Semantic Search

Information retrieval, search solutions

Indexing of documents based on terms

Fast term lookup to find documents

Spell Checking, Query Expansion, Related Terms, Did You Mean, Result facetation …

Þ Need more than just terms in documentÞ Thessaurus approach to erichment and retrievalÞ Thessaurus is modelled knowledge

Institut für Wissenstechnologien

13

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic Technologies

Example: Identify semantics in news articles

„Wegen einer Presseaussendung der Staatsanwaltschaft Wien zu einer Hausdurchsuchung klagt der frühere Finanzminister Karl-Heinz Grasser die Republik Österreich. Mit der Klage will er seinen Anspruch auf Schadenersatz feststellen.

Die Staatsanwaltschaft Wien habe durch ihre Aussendung anlässlich der Hausdurchsuchungen beim Ex-Minister am 26. Mai 2011 Grassers Persönlichkeitsrechte verletzt und insbesondere seinen „wirtschaftlichen Ruf“ beschädigt, heißt es in der Klage beim Landesgericht für Zivilrechtssachen.

Konkret klagt Grassers Anwalt Michael Rami auf Feststellung eines Schadenersatzanspruches im Rahmen der Amtshaftung für die Justizorgane. Die Klage richtet sich gegen den Bund, der durch die Finanzprokuratur vertreten wird.“

Propose some methods, consider a priori and a posteriori

Institut für Wissenstechnologien

14

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic Web?

The WWW has problems

Content formatted to be human-readable

Many visions require machine understanding

Search

Cross-Language

Fact Validation

Contextualization

=> Semantic Web

Institut für Wissenstechnologien

15

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic Systems

The WWW is not alone with its problems

Enterprise Information Systems

Smart mobile systems

…Þ Semantic Systems

Ballance between

a-priori modelling to ease ai tasks

a-posteriori methods for problem solving

Institut für Wissenstechnologien

16

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

What do we need to do?

Extract knowledge (manually or automatic)

Model knowledge

Reason about knowledge (Expand, Verfiy, Proof…)

Make knowledge available (Query …)

Display knowledge (Visualization)

Institut für Wissenstechnologien

17

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

What do we have?

*lots* of technologies

A priori

knowledge representation: skos, rdf, rdfs, (xtm), owl

triple stores: jena, sesame

querying: sparql

A posteriori

Information retrieval

Machine learning

Social software, tagging, crowdsourcing…

Institut für Wissenstechnologien

18

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

What will we talk about

Focus on A priori

knowledge representation

data modelling

semantic technologies

storage

retrieval

related topics

Institut für Wissenstechnologien

19

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic (Web) Stack

http://en.wikipedia.org/wiki/File:Semantic-web-stack.png

Institut für Wissenstechnologien

20

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Representing Semantics

S OP

With Triples

Institut für Wissenstechnologien

21

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Modelling Standards

<Image removed from public slides – see http://

www.mkbergman.com/wp-content/themes/ai3/images/2008Posts/080606_SemanticTechnologies.jpg on site http://

www.mkbergman.com/445/no-semantic-technologies />

Institut für Wissenstechnologien

22

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Storage Standards

<Image removed from public slides, see http://www.garshol.priv.no/blog/231.html >

Institut für Wissenstechnologien

23

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Semantic (Web) Stack

<Image removed from public slides – see http://

bnode.org/media/2009/07/08/semantic_web_technology_stack.png >

Institut für Wissenstechnologien

24

V. Pammer-Schindler, W. Kienreich Oct 11, 2012 VU SemTech 2012 - Intro

Questions?