1. Recommending and finding multimedia
resources in knowledge acquisition
based on Web resources
This work was supported by funds from the
German Federal Ministry of Education and
Research under the mark 01 PF 08015 A and from
the European Social Fund of the European Union
(ESF).
httc –
Hessian Telemedia Technology
Competence-Center e.V - www.httc.de
KOM - Multimedia Communications Lab
Prof. Dr.-Ing. Ralf Steinmetz (director)
Dept. of Electrical Engineering and Information Technology
Dr.-Ing. Christoph Rensing Dept. of Computer Science (adjunct professor)
Tel. +49 6151 16 6888 TUD – Technische Universität Darmstadt
Christoph.Rensing@KOM.tu-darmstadt.de Merckstr. 25, D-64283 Darmstadt, Germany
Tel.+49 6151 166150, Fax. +49 6151 166152
www.KOM.tu-darmstadt.de
ICCCN_2010_08_05 12. August 2010
© 2010 author(s) of these slides including research results from the KOM research network and TU Darmstadt. Otherwise it is specified at the respective slide

2. Outline
Scenario: Learning / Knowledge Acquisition based on Web
Resources
CROKODIL – a platform for collaborative Knowledge Acquisition
based on Web Resources
Concept & Usage of Semantic Networks
Finding and Recommendation of Resources
Conclusion & Outlook
KOM – Multimedia Communications Lab 2

3. Resources used for Learning and
Knowledge Acquisition
Learning
Resources Web Based Animation
Trainings
E-Lecture Teaching
… Material
Social (Web)
Resources Blogs WiKis
FAQs
Picture Coll.
Bulletin/
Discussion
Video Coll.
Boards
(Sources: slidestar.net, youtube.com, wehow.com)
KOM – Multimedia Communications Lab 3

4. Challenges of Resource-Based
Learning using Web Resources
RBL applied to learning with web resources rise many challenges:
Huge variety and quantity of possibly relevant resources
Finding relevant / authoritative / trusted resources is no easy task
Not explicitly intended for learning – different audiences
All relevant information is not necessarily in one place
How to store web resources efficiently in order to find them again
Further Challenges
Navigational disorientation
„lost in hyperspace“
Conceptual disorientation
Lack of integrating information in the own knowledge structure
Cognitive Overload
Finding information, analyzing found hits, organizing found information, …
See [SBB09+]
KOM – Multimedia Communications Lab 4

5. Challenges of Resource based
Learning using Web Resources
Define Strategy
for Search Search
Share
Use Select
Annotate Classificate
Persist
KOM – Multimedia Communications Lab 5

6. Support of Resource based
Learning
Social Bookmarking Expertsearch Searchengines
Blogs (Del.icio.us,…) (Xing,…) (Google,…)
(RSS,…)
Linklists
Electronic Define Strategy (Yahoo,…)
Communikation for Search Search
(E-Mail,…) Share
Rating Systems
(StumbleUpon,…)
Use Select
Editors
(Wikis, Excel,
Word,...) Ranking
Classificate (Pagerank,…)
Annotate
Persist
Online-
Annotation-Tools Browser
(Diigo,…) Plugins Save as Tagg (Flickr,
(Scrapbook,…) (Harddisk,…) Del.icio.us,…)
KOM – Multimedia Communications Lab 6

7. Why a new application?
Using different applications add load to the user
Our scenario is characterized by:
Heterogeneous resources
Text based formats like Wikis, FAQs, Blogs, PDF-Documents
Videos
Images
...
Users are following individual tasks
“Small” community
Existing applications do not fit for this characteristics in many
cases
Goal: CROKODIL: Support the user in the management of Web
Resources using for Knowledge Acquisition
KOM – Multimedia Communications Lab 7

8. Outline
Scenario: Resource based Learning / Knowledge Acquisition
CROKODIL – a platform for collaborative Knowledge Acquisition
based on Web Resources
Concept & Usage of Semantic Networks
Finding and Recommendation of Resources
Conclusion & Outlook
KOM – Multimedia Communications Lab 8

9. Semantic Networks
Used for knowledge representation
Formal model
Concepts
(Semantic) Relations
Directed or undirected graph
Distinction usually in types and instances
“Anne is a instance of the type person”
Challenge: How can be semantic information added effitiently?
Image source:http://www.tojet.net/articles/236.htm KOM – Multimedia Communications Lab 9

10. Tagging
Simple mean to organize websites, bookmarks, pictures,…
without constraints of strict classification
Folksonomic structures by aggregating tags of all users
Example: Delicious
Social bookmarking application (saving, annotating, managing, sharing
web pages)
Tag suggestions
Browsing via tags
Networks between users
KOM – Multimedia Communications Lab 10

11. Concept – Semantic Tagging
Construction of a personal net of resources by semantic tagging
TU Berlin Prepare Talk
Lecture related to
TUD
Presenter Tag
Workshop
Prof
Wind
Topic
Script
to read
Talk Location
Wiki
Tornado Paper
Blizzard
Person
Photos
Hurricane
Avi
Blog
News eyewitness report
Event
1 Annotation
2 Semantic Tagging Goal/Task
3 Sharing with a community See [BSRS09] [BSR+]
KOM – Multimedia Communications Lab 11

12. CROKODIL - Persist
KOM – Multimedia Communications Lab 12

13. CROKODIL - Classificate / annotate
KOM – Multimedia Communications Lab 13

14. KOM – Multimedia Communications Lab 14

15. Outline
Scenario: Resource based Learning / Knowledge Acquisition
CROKODIL – a platform for collaborative Knowledge Acquisition
based on Web Resources
Concept & Usage of Semantic Networks
Finding and Recommendation of Resources
Conclusion & Outlook
KOM – Multimedia Communications Lab 15

16. Finding Resources
By browsing the Semantic Network By browsing the CROKODIL Portal
KOM – Multimedia Communications Lab 16

17. Recommendations
Recommender systems
Present information items
to users that are likely of
interest
Based on implicit / explicit
user profiles
Use technologies from
Information Retrieval
Amazon book and CD recommendations (Source: amazon.com)
Different paradigms of generating / making recommendations
Collaborative Filtering munities
No applic able in small com
Based on similarity between users,tgood if there isiased redatas
enough sult
& often b
Often so-called cold-start problem (not enough ratings available)
Content-based recommendation sources
Based on properties or contents of resourcesable fo r heterogenous re
Not applic
Recommendation based on folksonnomies and frequency of utilization
Active recommendation by users for:username
Using a combination of different methods in CROKODIL
KOM – Multimedia Communications Lab 17

18. Structure based Recommendation
in Semantic Networks
Recommending by traversing the
Semantic Network
is
Communication subtopic Wiki
Re Networks
com Protocols
me
nda
paper tion script
Recommendation independent of
Type of Resources
KOM – Multimedia Communications Lab 18

19. Content-Based Recommendations
Computer
Communication Networks Wiki
Networks
Reco is
mme subtopic
Protocols
paper ndat
ion ? script
WP
WP WP
WP WP
WP
Similarity / relatedness between snippets is calcualted by
comparision with Wikipedia articles
See [SBD+10] KOM – Multimedia Communications Lab 19

20. Outline
Scenario: Resource based Learning / Knowledge Acquisition
CROKODIL – a platform for collaborative Knowledge Acquisition
based on Web Resources
Concept & Usage of Semantic Networks
Recommending and Finding of Resources
Conclusion & Outlook
KOM – Multimedia Communications Lab 20

21. Conclusion & Outlook
CROKODIL
an social application for managing heterogeneous Web Resources used
for Knowledge Acquisition
based on a combination of semantic networks and tagging
Integrated recommender systems based on different methods
Outlook
Deployment of the prototype in industry and university
Long term evaluation of the overall approach and the different methods
for recommendation
Extensions
Optimization of recommendation methods
Recommending tags
Merging personal knowledge networks
KOM – Multimedia Communications Lab 21

22. References
[SBB09+] Philipp Scholl, Bastian F. Benz, Doreen Böhnstedt, Christoph Rensing,
Bernhard Schmitz, Ralf Steinmetz: Implementation and Evaluation of a Tool for
Setting Goals in Self-Regulated Learning with Web Resources. In: Ulrike Cress, Vania
Dimitrova, Marcus Specht: Learning in the Synergy of Multiple Disciplines, EC-TEL
2009, vol. LNCS Vol 5794, p. 521-534, Springer-Verlag Berlin Heidelberg, October
2009. ISBN 978-3-642-04635-3.
[BSRS09] Doreen Böhnstedt, Philipp Scholl, Christoph Rensing, Ralf Steinmetz:
Modeling Personal Knowledge Networks to Support Resource Based Learning. In:
Klaus Tochtermann, Hermann Maurer: Proceedings of 9th International Conference
on Knowledge Management and Knowledge Technologies (I-KNOW'09), p. 309-316,
September 2009. ISBN 978-3-85125-060-2.
[BSR+09] Doreen Böhnstedt, Philipp Scholl, Christoph Rensing, Ralf Steinmetz:
Collaborative Semantic Tagging of Web Resources on the Basis of Individual
Knowledge Networks. In: Houben, G.-J.; McCalla, G.; Pianesi, F.; Zancanaro, M.:
Proceedings of First and Seventeenth International Conference on User Modeling,
Adaptation, and Personalization UMAP 2009, p. 379-384, Springer-Verlag Berlin
Heidelberg 2009, ISBN 978-3-642-02246-3.
[SBD+10] Philpp Scholl, Doreen Böhnestedt, Renato Dominguez-Garcia, Christoph
Rensing, Ralf Steinmetz: Extended Explicit Semantic Analysis for Calculating
Semantic Relatedness of Web Resources. Accepted for publication in: Proceedings
of the Fifth European Conference on Technology Enhanced Learning, Barcelona,
September 2010.
KOM – Multimedia Communications Lab 22

23. This work was supported by funds from the
German Federal Ministry of Education and
Research under the mark 01 PF 08015 A and
from the European Social Fund of the
European Union (ESF).
KOM – Multimedia Communications Lab 23

24. KOM – Multimedia Communications Lab 24