Semantic Web Applications - PowerPoint PPT Presentation

1 / 30
About This Presentation
Title:

Semantic Web Applications

Description:

Contest for the most advanced and most useful application of semantic web technologies ... Goal (inofficial): Motivate Master and PhD Students to do ... Flikr ... – PowerPoint PPT presentation

Number of Views:43
Avg rating:3.0/5.0
Slides: 31
Provided by: heinerstuc
Category:

less

Transcript and Presenter's Notes

Title: Semantic Web Applications


1
Semantic Web Applications
  • Prof. Dr. Heiner Stuckenschmidt
  • Universität Mannheim
  • HWS 2007

2
Outline
  • The Semantic Web Challenge
  • Infomation Portals MultimediaN
  • Semantic Browsing COHSE
  • Personalized Search MusiDB
  • Collaborative Editing Semantic MediaWiki
  • Social Network Analysis Flink

3
Semantic Web Challenge
  • Contest for the most advanced and most useful
    application of semantic web technologies
  • Organized since 2003
  • http//challenge.semanticweb.org
  • Goal (official) Demostrate the potential of
    semantic web technologies for solving real world
    problems
  • Goal (inofficial) Motivate Master and PhD
    Students to do lots of programming work -)
  • Participants about 10 20 each Year

4
Waht is a Semantic Web Application?
  • Text from the Semantic Web Challenge home page
  • A Semantic Web Application has to meet the
    following minimal requirements
  • First, the meaning of data has to play a central
    role.
  • Meaning must be represented using formal
    descriptions
  • Data must be manipulated/processed in interesting
    ways to derive useful information and
  • this semantic information processing has to play
    a central role in achieving things that
    alternative technologies cannot do as well, or at
    all
  • Second, the information sources used
  • should have diverse ownerships (i.e. there is no
    control of evolution),
  • should be heterogeneous (syntactically,
    structurally, and semantically), and
  • should contain real world data, i.e. are more
    than toy examples.
  • Third, it is required that all applications
    assume an open world, i.e. assume that the
    information is never complete.

5
Example 1 MultimeniaN
  • Application domain cultural heritage
  • Preservation of cultural heritage for the
    following generations
  • Digitalization of collections from important
    libraries and museums
  • Provide access to objects across different
    collections and locations
  • Problems
  • Integration of heterogeneous data sources
  • Advanced search for objects of a certain style or
    period

6
Data Sources
  • Artchive.com online Art Portal(gt3000 Objekte)
  • Rijksmuseum Amsterdam (gt700 Objekte)
  • Ethnological Museum Amsterdam (gt 23.000 Objekte)
  • Tropical Museum Amsterdam (gt78.000 Objekte)
  • Royal Library of the Netherlands(gt1600 Objekte)

7
Background Knowledge
  • Objects from all collections are linked to
    jointly used thesauri and vocabularies
  • Getty Arts and Architecture Thesaurus (AAT)
  • Union List of Artists Names (ULAN)
  • Thesaurus of Geographic Names (TGN)
  • Ethnological Thesaurus (SVNC)
  • General Thesaurus of the English Language
    (Wordnet)

8
Interface
9
Architectur
10
Benefits of the Technology
  • Unified description of art objects from different
    sources and collections
  • Facetted search Role of query terms is
    explicated
  • Silber as material vs. Silver as part of the
    title
  • Background Information about Objects (style,
    period, related artists)
  • Explicit relations between objects

11
Example 2 Semantic Browsing
  • Application Searching Information
  • Looking for infromation on the web either for
    private or for business purposes
  • Problems
  • The usual ones
  • Idea
  • Extending existing browsers with the ability to
    use semantic web contents to support search

12
Semantic Web Browsers
  • Automatic recognition of objects, persons,
    concepts etc. mentioned on a web page on the
    basis of an underlying ontology
  • Support the Annotation of information contents,
    e.g. by proposing annotations and keywords
  • Automatic generation of hyperlinks
  • To other objects of the same type
  • To pages talking about the same concept
  • To background information about objects or
    concepts
  • Example Piggy Bank, Magpie, COHSE

13
COHSE
14
Benefits of the technology
  • Same as above, but
  • Applicable to standard web pages, provided that
  • A suitable ontology is available
  • The terms occurring on the page can be mapped
    into this ontology
  • Limited support for personalization by means of
    using special ontologies
  • Enrichment of exsiting web resources by
    supporting semantic annotation of contents

15
Example 3 Personalization
  • Application
  • Proactively suggest relevant contents to the user
  • Special Case suggest products the user might
    want to buy
  • Problems
  • Lack of information about the users interest
  • Interests are often ambiguous (z.B. hard music)
  • Classification of objects missing or heterogeneous

16
Example MusiDB
  • Search for Music
  • Music-Ontology Artists, Songs, Albums
    http//musicbrainz.org/
  • Example Which Album do I have to buy to get this
    song?
  • MusiDB System http//www.cs.vu.nl/rstegers/iwa/

17
Interface
18
What about unknown music?
Which Style do you prefer ?
19
Recommender Systems
Users
2. Feedback
Music
1. Recommendation
3. Improved Recommendation
...
20
(No Transcript)
21
Benefits of the Technology
  • As before
  • Unique identifiers for Artists etc.
  • Explicit Knowledge about relations
  • In addition
  • Genre-hierarchy as basis for recommendations
  • Classification of artists and songs based on user
    feedback

22
Example Collaborative Knowledge Creation
  • Users jointly annotate Web pages and create
    knowledge models (a la Web 2.0)
  • Prominent examples Social Tagging
  • Del.icio.us
  • Flikr
  • Real Value is added when users jointly create
    more complex knowledge structures (i.e. relations)

23
Example Semantic Mediawiki
  • Follows the Wikipedia paradim
  • In addition to text, structured information can
    be added using a simple syntax
  • Classification of Objects
  • Properties of and relations between objects
  • Demonstration Domain
  • Persons, Conferences

24
Interface
25
Benefits of the Technology
  • Large scale acquisition of structured knowledge
  • Automatic Generation of Reports and Factsheets
  • Semantic Search (e.g. for certain object types)
  • Consistent use of type information across
    different languages
  • Enables the use outside the wiki by means of
    exporting the knowledge as RDF file, e.g. as a
    basis for analyzing relations

26
Network Analysis
  • Use Information about relations between objects
    for futher analyses
  • Citation analysis
  • Social network analysis
  • Duplicate Detection
  • Semantic Technologies as basis for such analysis
  • Unambiguous representation of relations
  • Standard syntax, tool support available

27
Example Flink
  • Aanalysis of relations between people involved in
    semantic web technologies
  • Data extracted automatically from the web
  • Authors of the International Semantic Web
    Conference
  • Their publications
  • Relations to other authors identified using
    Google
  • Analyses
  • Important people in the community
  • Relevant topics and their interaction

28
Interface
29
Benefits of the technology
  • As before
  • Unique identifiers for objects
  • Explicit relations between objects
  • In addition
  • Derivation of global properties from relations

30
Conclusions
  • Semantic Web Technologies provide means to
    represent strutured information on the web
  • unique identifiers
  • classifications
  • relations between objects
  • This representation is an important basis for
    advanced applications
  • Search, Personalization, Information aggregation,
    Analyses,
Write a Comment
User Comments (0)
About PowerShow.com