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co-funded by the European Union
WeKnowItEmerging, Collective Intelligence for personal,
organisational and social use http://www.weknowit.eu
Event Detection Processing and RepresentationAdvances, Future Applications, Challenges
Yiannis KompatsiarisCERTH-ITI
co-funded by the European Union
Groups
Caption
Time
Low-level
User
Profile
Favs
Comms
Geo Social
network
Tags
Event Processing in User Generated Content / Social Media / Web 2.0
co-funded by the European Union
Event Detection Research approaches
Community Detection (Graph-based) Image clusters based on finding tag-image communities in social network Graph-based, fast and scalable community detection approach
Time aware user-tag co-clustering Co-clustering based Detects on the same time topics and users relevant to the event
LDA probabilistic approach generalization of Latent Dirichlet Allocation (LDA) approach Events are indicated by unusual content or annotation that is localized in space
and time
co-funded by the European Union
Results and Applications User-Genrated maps of Points of Interests
Where there is (was) something interesting happeningdemo: www.clusttour.gr
Name events by most important tags
co-funded by the European Union
Time-aware user-tag co-clustering
Accessories, bags,
fashion,
Cars, football, holidays,
horses, sea, turkey, fashion
New York, hat, trousers, fashion,
Gucci
animals, elephants, nature sea,
turkey, bags
hats, Gucci
fashion, jeans, NY
User 1 User 2 User 3
fashionweek, fashion, silk,
wool
co-funded by the European Union
Research for upcoming Events Bursts detection in networks of tag co-occurences
Event is an emerging context tag cluster Detect building-up events by updating tag
connectivity strenght from user input stream Monitor “hot topics” related to specified tags
Challenges System response must by within seconds
Fast updates on large scale graph
Alarm triggered when event reaches threshold Monitor emerging clusters
co-funded by the European Union
Representation – Event Model F
Based on the foundational ontology DOLCE+DnS Ultralight (DUL) - OWL
Representation for time and space, objects and persons Mereological, causal and correlative relationships
between events Provides flexible means for
event composition modeling event causality and event correlation representing different interpretations of the same event.
Available from: http://west.uni-koblenz.de/eventmodel/
co-funded by the European Union
Events Representation - Applications
Monitoring/mergingevent log files
Explore and visualize largesemantically heterogeneousdistributed semantic datasetsin real-time.
co-funded by the European Union
Challenges Granularity of event recognition – trade-off
Few, large, better quality events (e.g. fairs, concerts) Lots, smaller, noisy events (e.g. birthday parties)
Event naming Can localize event and display relevant tags, but not always assign
simple name (as person would do) Sparsity of user data
Need large number of geo-localized, timestamped and tagged resources (images) for certain location (e.g.) city and longer time (few years)
Representation Generating APIs for pattern-based ontologies Reasoning Adaptation to domain-specific requirements
co-funded by the European Union
Thank you!
WeKnowIthttp://www.weknowit.eu
Yiannis Kompatsiarishttp://mklab.iti.gr