+ All Categories
Home > Documents > Presenting Knowledge on the Semantic Web

Presenting Knowledge on the Semantic Web

Date post: 06-Jan-2016
Category:
Upload: lynne
View: 24 times
Download: 1 times
Share this document with a friend
Description:
Presenting Knowledge on the Semantic Web. Lynda Hardman Semantic Media Interfaces http://media.cwi.nl. Long-term goal. Develop knowledge-intensive models and document processing technologies that are able to: generate coherent multimedia presentations tailored to an individual user - PowerPoint PPT Presentation
Popular Tags:
27
Presenting Knowledge on the Semantic Web Lynda Hardman Semantic Media Interfaces http://media.cwi.nl
Transcript
Page 1: Presenting Knowledge on the Semantic Web

Presenting Knowledgeon the Semantic Web

Lynda Hardman Semantic Media Interfaces

http://media.cwi.nl

Page 2: Presenting Knowledge on the Semantic Web
Page 3: Presenting Knowledge on the Semantic Web
Page 4: Presenting Knowledge on the Semantic Web

Long-term goal• Develop knowledge-intensive models and document

processing technologies that are able to:

generate coherent multimedia presentations tailored to an individual user

taking into account their preferences, abilities, device capabilities and environment.

Page 5: Presenting Knowledge on the Semantic Web

Goals of research

•Understand how to – incorporate design and discourse

knowledge into multimedia presentations

– represent this knowledge in Web and Semantic Web technologies

•Semantic Web provides– source content for inclusion in presentations

– a means of expressing knowledge needed

Page 6: Presenting Knowledge on the Semantic Web

AmsterdamHypermedia

Model

Cuypers

Topia,DISC

Noadster

Vox Populi

From syntax to semantics

TimeSyn

tax

Sem

antic

s

Page 7: Presenting Knowledge on the Semantic Web

AmsterdamHypermedia

Model

Cuypers

Topia,DISC

Noadster

Vox Populi

From syntax to semantics

TimeSyn

tax

Sem

antic

s

Page 8: Presenting Knowledge on the Semantic Web

Space/time trade-offs

Page 9: Presenting Knowledge on the Semantic Web

Space/time trade-offs

• Media repository from Rijksmuseum• Quantitative constraints insufficient

using pixel-based positioning• Qualitative constraints also used

specification of constraints at higher level A not-overlap B, B after C

• If insoluble then backtrack to other solutions using Prolog

• Joost GeurtsMMM 2001, WWW 2001

Page 10: Presenting Knowledge on the Semantic Web

AmsterdamHypermedia

Model

Cuypers

Topia,DISC

Noadster

Vox Populi

From syntax to semantics

TimeSyn

tax

Sem

antic

s

Page 11: Presenting Knowledge on the Semantic Web

Inferring document structure

Page 12: Presenting Knowledge on the Semantic Web

•First name•Surname•Other name•Synonym•Year of birth•Year of death

Artist

•Title•Short title•Material•Style period•Creation year•Picture

Artefact

ArtTheme

part of

•ID•Type•Keyword text

Keyword

•ID•Type•Text

Presentation

•Sequence no.•Title•Description

Presentation part

Place andTime interval

contained in

description

description

creator

includes

includes

points to

subClassOf

Rijksmuseum domain model

Topia project

Page 13: Presenting Knowledge on the Semantic Web

Inferring document structure•Topia•Rijksmuseum ARIA database -> RDF•Clustering on results of query•Presentation showing “table of

contents” and current focus

• Lloyd RutledgeACM Hypertext 2003

Page 14: Presenting Knowledge on the Semantic Web

Semantic graph to presentation

Page 15: Presenting Knowledge on the Semantic Web

Semantic graph to presentation• DISC• Rijksmuseum repository of media items• Semantic graph is not enoughRembrandt married-to Saskia also need discourse structuresfor deriving grouping, ordering and priorities

• Biography template createdpainter is-a profession

• Stefano Bocconi, Joost GeurtsISWC 2003

Page 16: Presenting Knowledge on the Semantic Web

AmsterdamHypermedia

Model

Cuypers

Topia,DISC

Noadster

Vox Populi

From syntax to semantics

TimeSyn

tax

Sem

antic

s

Page 17: Presenting Knowledge on the Semantic Web
Page 18: Presenting Knowledge on the Semantic Web

Semantic Web browsing

•Noadster•Generalised semantic web browsing•Integrating global and local browsing

• Lloyd Rutledge,WWW 2005

Page 19: Presenting Knowledge on the Semantic Web

AmsterdamHypermedia

Model

Cuypers

Topia,DISC

Noadster

Vox Populi

From syntax to semantics

TimeSyn

tax

Sem

antic

s

Page 20: Presenting Knowledge on the Semantic Web

AmsterdamHypermedia

Model

Cuypers

Topia,DISC

Noadster

From syntax to semantics

TimeSyn

tax

Sem

antic

s

Eculture

Page 21: Presenting Knowledge on the Semantic Web

MultimediaN Eculture

•Collection of vocabularies in RDF:– AAT, ULAN, TGN

•Artchive images•Interface for searching and browsing

http://eculture.multimedian.nl

• Partners:– Guus Schreiber, VU; Bob Wielinga & Jan Wielemaker, UvA

Page 22: Presenting Knowledge on the Semantic Web

Eculture advanced search

Page 23: Presenting Knowledge on the Semantic Web

Eculture search result

Page 24: Presenting Knowledge on the Semantic Web

Eculture single artefact

Page 25: Presenting Knowledge on the Semantic Web

Scientific challenges

• Making (multimedia) discourse and design knowledge explicit

• Expressing re-usable semantics of media assets

• Designing architectures for multimedia presentation generation

Page 26: Presenting Knowledge on the Semantic Web

Conclusions & Future Work• From projects described we have learned much:

– distinguish stages in process– make discourse knowledge explicit– mappings between domain and discourse knowledge

• Explicit user model being worked on:– CHIP user interaction, partner Rijksmuseum

Passepartout media installation, partner V2_

• Investigating use of timeline:– to display artefacts to a user, MultimediaN Eculture

• Semantic Web Best Practices and Deployment Group, Multimedia Task Force– http://www.w3.org/2001/sw/BestPractices/MM/

• SWUIG Semantic Web User Interface Group

Page 27: Presenting Knowledge on the Semantic Web

• NWO I2RPIntelligent Information Retrieval and Presentation

• NWO NASHNetworked Adaptive Structured Hypermedia

• Telematica Instituut Topia

• ICES KIS MultimediaN Eculture

• Images courtesy of Rijksmuseum, Amsterdam

• Acknowledgements:

– Jacco van Ossenbruggen, Frank Nack,Stefano Bocconi, Joost Geurts, Lloyd Rutledge,Alia Amin, Michiel Hildebrand, Zhisheng Huang

This research is supported by


Recommended