Details
| Originalsprache | Englisch |
|---|---|
| Titel des Sammelwerks | 2nd International Conference on Mobile, Hybrid, and On-Line Learning, eL and mL 2010 |
| Seiten | 105-110 |
| Seitenumfang | 6 |
| Publikationsstatus | Veröffentlicht - 15 März 2010 |
| Veranstaltung | 2nd International Conference on Mobile, Hybrid, and OnLine Learning, eL and mL 2010 - Saint Maarten, Niederlande Dauer: 10 Feb. 2010 → 16 Feb. 2010 |
Publikationsreihe
| Name | 2nd International Conference on Mobile, Hybrid, and On-Line Learning, eL and mL 2010 |
|---|
Abstract
The Web offers autonomous and frequently useful resources in growing manner. User Generated Content (UGC) like Wikis, Weblogs or Webfeeds often do not have one responsible authorship or declared experts who checked the created content for e.g. accuracy, availability, objectivity or reputation. The user is not able easily, to control the quality of the content he receives. If we want to utilize the distributed information flood as a linked knowledge base for higher-layered applications - e.g. for knowledge transfer and learning - information quality (iq) is a very important and complex aspect to analyze, personalize and annotate resources. In general, low information quality is one of the main discriminators of data sources on the Web [1]. Assessing information quality with measurable terms can offer a personalized and smart view on a broad, global knowledge base. We developed the qKAI application framework [2] to utilize available, distributed data sets in a practically manner. In the following we present our adaption of information quality aspects to qualify Web resources based on a three-level assessment model. We deploy knowledge-related iq-criteria as tool to implement iq-mechanisms stepwise into the qKAI framework. Here, we exemplify selected criteria of information quality in qKAI like relevance or accuracy. We derived assessment methods for certain iq-criteria enabling rich, game-based user interaction and semantic resource annotation. Open Content is embedded into knowledge games to increase the users' access and learning motivation. As side effect the resources' quality is enhanced stepwise by ongoing user interaction.
ASJC Scopus Sachgebiete
- Informatik (insg.)
- Computernetzwerke und -kommunikation
- Informatik (insg.)
- Mensch-Maschine-Interaktion
- Sozialwissenschaften (insg.)
- Ausbildung bzw. Denomination
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- Apa
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- BibTex
- RIS
2nd International Conference on Mobile, Hybrid, and On-Line Learning, eL and mL 2010. 2010. S. 105-110 5430000 (2nd International Conference on Mobile, Hybrid, and On-Line Learning, eL and mL 2010).
Publikation: Beitrag in Buch/Bericht/Sammelwerk/Konferenzband › Aufsatz in Konferenzband › Forschung › Peer-Review
}
TY - GEN
T1 - Towards enhanced user interaction to qualify web resources for higher-layered applications
AU - Steinberg, Monika
AU - Brehm, Jürgen
PY - 2010/3/15
Y1 - 2010/3/15
N2 - The Web offers autonomous and frequently useful resources in growing manner. User Generated Content (UGC) like Wikis, Weblogs or Webfeeds often do not have one responsible authorship or declared experts who checked the created content for e.g. accuracy, availability, objectivity or reputation. The user is not able easily, to control the quality of the content he receives. If we want to utilize the distributed information flood as a linked knowledge base for higher-layered applications - e.g. for knowledge transfer and learning - information quality (iq) is a very important and complex aspect to analyze, personalize and annotate resources. In general, low information quality is one of the main discriminators of data sources on the Web [1]. Assessing information quality with measurable terms can offer a personalized and smart view on a broad, global knowledge base. We developed the qKAI application framework [2] to utilize available, distributed data sets in a practically manner. In the following we present our adaption of information quality aspects to qualify Web resources based on a three-level assessment model. We deploy knowledge-related iq-criteria as tool to implement iq-mechanisms stepwise into the qKAI framework. Here, we exemplify selected criteria of information quality in qKAI like relevance or accuracy. We derived assessment methods for certain iq-criteria enabling rich, game-based user interaction and semantic resource annotation. Open Content is embedded into knowledge games to increase the users' access and learning motivation. As side effect the resources' quality is enhanced stepwise by ongoing user interaction.
AB - The Web offers autonomous and frequently useful resources in growing manner. User Generated Content (UGC) like Wikis, Weblogs or Webfeeds often do not have one responsible authorship or declared experts who checked the created content for e.g. accuracy, availability, objectivity or reputation. The user is not able easily, to control the quality of the content he receives. If we want to utilize the distributed information flood as a linked knowledge base for higher-layered applications - e.g. for knowledge transfer and learning - information quality (iq) is a very important and complex aspect to analyze, personalize and annotate resources. In general, low information quality is one of the main discriminators of data sources on the Web [1]. Assessing information quality with measurable terms can offer a personalized and smart view on a broad, global knowledge base. We developed the qKAI application framework [2] to utilize available, distributed data sets in a practically manner. In the following we present our adaption of information quality aspects to qualify Web resources based on a three-level assessment model. We deploy knowledge-related iq-criteria as tool to implement iq-mechanisms stepwise into the qKAI framework. Here, we exemplify selected criteria of information quality in qKAI like relevance or accuracy. We derived assessment methods for certain iq-criteria enabling rich, game-based user interaction and semantic resource annotation. Open Content is embedded into knowledge games to increase the users' access and learning motivation. As side effect the resources' quality is enhanced stepwise by ongoing user interaction.
KW - Information quality
KW - Knowledge transfer
KW - Open content
KW - Semantic annotation
UR - http://www.scopus.com/inward/record.url?scp=77952145029&partnerID=8YFLogxK
U2 - 10.1109/eLmL.2010.25
DO - 10.1109/eLmL.2010.25
M3 - Conference contribution
AN - SCOPUS:77952145029
SN - 9780769539553
T3 - 2nd International Conference on Mobile, Hybrid, and On-Line Learning, eL and mL 2010
SP - 105
EP - 110
BT - 2nd International Conference on Mobile, Hybrid, and On-Line Learning, eL and mL 2010
T2 - 2nd International Conference on Mobile, Hybrid, and OnLine Learning, eL and mL 2010
Y2 - 10 February 2010 through 16 February 2010
ER -