Delft University of Technology Generating Resource Profiles by Exploiting the Context of Social Annotations ISWC, Bonn, Germany, Oct 27 th 2011 ardo Kawase 1 , George Papadakis 2 , Fabian Abel 3 1 L3S Research Center, Leibniz University Hannover, Germany 2 ICCS, National Technical University of Athens, Greece 3 Web Information Systems, TU Delft
28
Embed
Generating Resource Profiles by Exploiting the Context of Social Annotations
This document is posted to help you gain knowledge. Please leave a comment to let me know what you think about it! Share it to your friends and learn new things together.
Transcript
DelftUniversity ofTechnology
Generating Resource Profiles by Exploiting the Context of Social AnnotationsISWC, Bonn, Germany, Oct 27th 2011
Ricardo Kawase1, George Papadakis2, Fabian Abel3
1L3S Research Center, Leibniz University Hannover, Germany2 ICCS, National Technical University of Athens, Greece
3Web Information Systems, TU Delft
2Generating Resource Profiles by Exploiting the Context of Social Annotations
Social Annotations Folksonomies
• Folksonomy: • set of tag assignments• Formal model [Hotho et al. ‘07]:F = (U, T, R, Y)
baker, cool
armstrongdizzy, jazz
armstrongjazzmusic
trumpet
trumpetUsers
Tags
Resources
armstrong, baker, dizzy, cool,
jazzmusic, jazz, trumpet
usertag
resource
tag assignment
3Generating Resource Profiles by Exploiting the Context of Social Annotations
Generating resource profiles
• Resource profile = representation of a resource = set of weighted concepts
• Straightforward approach = occurrence frequency of tags:
SELECT tag, count(distinct user) FROM tas WHERE resource = XY
GROUP BY tag
baker, cool
Profile? concept weight
?
cool Applicationsthat operate on
resource profiles(e.g. search,
content-based recommender)
Profile? concept weight
baker 1 cool 2
Applications rely on good resource profiles!
4Generating Resource Profiles by Exploiting the Context of Social Annotations
validation):• remove one tag from the resource • create (context-based) resource profile • use profile to create a ranking of tags hidden tag should be
at the top of the ranking• Baseline: tag co-occurrence • Metrics: Success@k = probability that the relevant
tag appear within the top k of the ranking• Data sets:Tag Assignments (TAs) 1,288
TAs with Spatial Information
671
TAs with Category Information
917
TAs with URI Information 1,050
TAs with all information 432
Resources 566,939Users 6,569Tag Assignments (TAs)
2,622,423
TagMe!
BibSonomy
24Generating Resource Profiles by Exploiting the Context of Social Annotations
Semantic meaning and spatial information allow for best performance.
Area size more valuable than distance to center
no significant difference w.r.t. category- and user-based strategy
25Generating Resource Profiles by Exploiting the Context of Social Annotations
Combining different types of context-based profiling strategies
Mixture of context-based strategies improve performance (by 37%)Context-based strategies have to be combined intelligently in order to increase cumulative gain in performance.
26Generating Resource Profiles by Exploiting the Context of Social Annotations
The more specific the context, the better the performance ( reducing noise)
27Generating Resource Profiles by Exploiting the Context of Social Annotations
Conclusions• What we did: framework for generating resource profiles by exploiting contextual information of social annotations• Context-based folksonomy model• Set of context-based resource profiling strategies (both
generic and application-specific strategies)• Evaluation in two social tagging systems: TagMe! and BibSonomy
• Results: • Context-based strategies outperform other strategies that
do not exploit contextual information• Context of tag assignments (e.g. semantic meaning) allows for best
performance
• Context of the user who performs the tag assignment is competitive
• Mixing context-based strategies improves quality but does not necessarily result in a cumulative gain in performance (“over-contextualization”) smart mixing performs best (>40% improvement)
28Generating Resource Profiles by Exploiting the Context of Social Annotations