the social semantic server tool support in learning layers
TRANSCRIPT
http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Learning LayersScaling up Technologies for Informal Learning in SME Clusters
SSS Healthcare Support
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Agenda
http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Tool Integration: Healthcare
• Bits and Pieces– Completely based on SSS, thus uses nearly all services (e.g., Data Import, User
Event, Tag, Learning Episode, Recommendation, Category, Activity, Search ...)• Discussion Tool
– Entity and Learning Episode services enable Bits to be attached to Q/As• Living Documents
– Living Document service links Q/As to documents– Planned: Recommend potential contributors or documents of interest
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http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Examples in Bits and Pieces
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Tag Recommender
Resource Recommender
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Examples in Discussion Tool
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Bits can be attached to discussions
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Examples in Living Documents
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Create new / link Living Document to discussion
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Agenda
http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Resource Recommender based on Cognitive Processes
• Recommender research exploits digital traces of social actions and interactions– e.g., Collaborative Filtering (CF) suggests resources of
most similar users
• BUT: In CF, users treated as just another entity (such as a resource, a tag etc.)
• Structuralist simplification that neglects attention and interpretation dynamics
• No ranking of resources in CF
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SUSTAIN (Love et al., 2004)
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• Resource represented by features • Cluster(s) H
• Vector of values along the n feature dimensions
• Fields of interest• Attentional weights wi:
• Importance of feature for user
• Training (for each resource R)• Start with one cluster H• Form new cluster if sim(R,H) > T• Adjusting Hi and wi after each run
• Testing (for each candidate c)• Compare features of candidate to highest
activated cluster (Hmax)
http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Evaluation• Social Bookmarking datasets (e.g.,
BibSonomy)• Resource features derived by Latent
Dirichlet Allocation (LDA) topics• Per user: 20% most recent used
resources for testing, 80% for training• In many cases only one resource for
training!• Keeps chronological order
→ predict future based on the past• State-of-the-art baseline algorithms• Recall / Precision for k = 1 – 20
recommended resources
• presented at WWW‘15 conference10
http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Tag Recommender Online Study
• 2 tag recommender algorithms inspired by cognitive science– 3Layers based on human categorization (semantic context)– BLL based on learning and forgetting (time context)
• Offline evaluations showed good results in terms of accuracy• Online study would show user acceptance in a workplace setting
• Collaborative digital curation scenario using our KnowBrain tool
• 18 university employees explored the topic of „designing workplaces that move people“ for a period of four weeks– Collected at least 4 resources per week either alone or in group
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Study Interface (KnowBrain)
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Preliminary Results
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http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Learning LayersScaling up Technologies for Informal Learning in SME Clusters
SSS Construction Support
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http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Agenda
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http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Tool Integration: Construction
• Learning Toolbox– Create, search, tag Tiles, Apps and other contents (e.g., videos from
AchSo!)• AchSo!
– Circle and Video services arrange videos and make them available to Learning Toolbox (or maybe even Bits and Pieces / Living Documents)
• Bookmarker / Attacher– Metadata, Tag, Search services for annotating and finding bookmarks
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Examples: Learning Toolbox
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Search forcontent in LTBusing SSS
http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Examples: Learning Toolbox
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SSS query result
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Examples: AchSo!
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Circle service to arrange videos in groups
or share videos with colleagues
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Agenda
http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Context Aware Resource Recommenders: Location
• Opportunity for Learning Toolbox and AchSo! because the location info is especially important in the construction domain
• Exploit user location to improve recommendations– e.g., especially for cold-start users
with no explicit interaction data• Use current location to find
nearby artefacts• Use location history of user to
identify interests– Find similar users → Collaborative
Filtering (CF)21
http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Evaluation
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• We simulate our workplace setting with a dataset from FourSquare• Focus on cold-start users
→ no training data, 2,783 evaluated users
• Data of more than 2 million users available for CF
• 3 Approaches based on CF• Jaccard similarity• Network-based
– Neighborhood overlap– Adamic adar
• MostPopular (baseline)
→ Presented at RecSys‘15
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Agenda
http://Learning-Layers-eu – Scaling up Technologies for Informal Learning in SME Clusters – [email protected]
Giving learners the power to understand and analyse their learning process!
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MonitoringActivities
Exploring Topics
Assessing Informal Learning Support
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Assessing Informal Learning Support
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Understanding explicit and
implicit social relations
• Evaluate Knowledge Acquisition, Participation, Knowledge creation (3 Metaphors of Learning)• Presented at ECTEL‘15 in Toledo, Spain and at ICWL‘15 in Guangzhou, China