The Story behind Everything Is Connected: Multimedia narration of automatically discovered paths in Linked Data
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Everything is Connected (http://everythingisconnected.be) is a Linked Data application for automatically generating a story between two concepts in the Web of Data, based on formally described links. A path between two concepts is obtained by browsing linked open datasets; the path is then enriched with multimedia presentation material for each node in order to obtain a full multimedia presentation of the found path. An efficient technique combining pre-processing and indexing of RDF datasets is used, which is able to find paths in a couple of seconds.
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The Story behind Everything Is Connected: Multimedia narration of automatically discovered paths in Linked Data
- 1. 9/13/13 1 The story behind Miel Vander Sande @Miel_vds Multimedia narration of automatically discovered paths in Linked Data
- 3. VIDEO CODING & COMPRESSION SEMANTIC & SOCIAL WEB Me MEDIA Annotation & ANALYSIS GAMING TECHNOLOGY
- 4. LINKED DATA?
- 6. We put a layer on the existing web Adding machine understandable descriptions TO the underlying data USING graph structures
- 8. It’s Like the WEB but instead of Linking Pages we Link data and enrich it semantically so Generic intelligent agents can UNDERSTAND and BROWSE DATA autonomously
- 11. Linked Data tangible? HOW DO WE Make
- 12. AGENDA1 CONCEPT 3 PATH NARRATION 2 PATHFINDING 4 DEMO
- 13. AGENDA1 CONCEPT 3 PATH NARRATION 2 PATHFINDING 4 DEMO
- 14. ÜBERDEMODEMONSTrate Linked DaTA & Semantic web. Represent our lab. Fast. Sexy. Modern.
- 20. Client Server SOURCE DBPedia Topic 1 Topic 2 Topic 3 Topic 4 Topic 5 … Topic N Playback SOLR Pathfindin g RESTAPI SIREn Resource Description Lookup DEST INAT IO N
- 21. AGENDA1 CONCEPT 3 PATH NARRATION 2 PATHFINDING 4 DEMO
- 22. Client Server SOURCE DBPedia Topic 1 Topic 2 Topic 3 Topic 4 Topic 5 … Topic N Playback SOLR Pathfindin g RESTAPI SIREn Resource Description Lookup DEST INAT IO N PATHFINDING SERVICEREASONABLE COMPLEXITY HIGH PERFORMANCE!
- 23. Laurens De Vocht laurens.devocht@ugent.be @laurens_d_v LEADing & Ongoing research
- 24. ? Paris Barack Obama Bertrand Delanoë Catholic Church Joe Biden mayor religion religion of vicepresident of Result QUERY Paris Barack Obama
- 25. AAdjacency MATRIX WEIGHTED EDGES HEURISTIC * ITERATIVE ALGORITHM
- 26. AAdjacency MATRIX WEIGHTED EDGES HEURISTIC * ITERATIVE ALGORITHM
- 28. 0 2 3 PARIS Eiffel tower FRANCE . . . 1 4 5 BARACK OBAMA JOE BIDEN UNITED STATES . . . Resources :Paris 0 :Barack_Obama 1 :Eiffel_Tower 2 :France 3 :Joe Biden 4 :United_States 5 … 0 1 2 3 4 5 0 0 0 1 1 0 0 1 0 0 0 0 1 1 2 1 0 0 0 0 0 3 1 0 0 0 0 0 4 0 1 0 0 0 0 5 0 1 0 0 0 0
- 29. AAdjacency MATRIX WEIGHTED EDGES HEURISTIC * ITERATIVE ALGORITHM
- 30. deg(node) = sum(nodelinks) weight(parent; child) = log(deg(parent)) + log(deg(child)) A Novel Metric for Information Retrieval in Semantic Networks – Moore et al. ENCOURAGE RARE NODES
- 31. 0 2 3 PARIS Eiffel tower FRANCE A Novel Metric for Information Retrieval in Semantic Networks – Moore et al. deg(0) =1286 deg(2) = 2237 deg(3) = 3138 weight(0;2) = 6,46 weight(0;3) = 6,61 ENCOURAGE RARE NODES deg(node) = sum(nodelinks) weight(parent; child) = log(deg(parent)) + log(deg(child))
- 32. AAdjacency MATRIX WEIGHTED EDGES HEURISTIC * ITERATIVE ALGORITHM
- 33. Jaccard distance :monument :language :capital :mayor :Paris :France unSHARED PREDICATES BETWEEN RESOURCES FAVOR CLOSELY RELATED RESOURCES
- 34. 0 2 3 PARIS Eiffel tower FRANCE weight(0;2) = 6,46 weight(0;3) = 6,61 weight(2;3) = 6,7 h(0;3) = 0.75 h(0;2) = 0.65 f(x;y) = h(x;y) + weight(x;y) PRIORITY QUEue of A* h(2;3) = 0.75
- 35. 0 2 3 PARIS Eiffel tower FRANCE . . . 1 4 5 BARACK OBAMA JOE BIDEN UNITED STATES . . . IF NO PATH FOUND EXPAND CHILDNODES ADD TO ADJACENCY MATRIX REPEAT OR TERMINATION
- 36. OPTIMIZATION: Node centrality based rank reduction 0 1 2 3 … 0 0 0 1 1 1 0 0 0 0 2 1 0 0 0 3 1 0 0 0 … Matrix INIT TIME GROWS exponentially Memory limitations! Reduce! OPTIMIZATION: Blacklisting
- 37. OPTIMIZATION: Node centrality based rank reduction SEACH FOR HUBS: NODES WITH Many Links PageRank
- 38. Hitrate above 90% Testset of 10 000 paths among 200 popular cities, artists and countries in DBPedia (10M entities)
- 39. Average OF 4 steps
- 42. Over 60% of paths found in less than 2000ms
- 43. AGENDA1 CONCEPT 3 PATH NARRATION 2 PATHFINDING 4 DEMO
- 44. Client Server SOURCE DBPedia Topic 1 Topic 2 Topic 3 Topic 4 Topic 5 … Topic N Playback SOLR Pathfindin g RESTAPI SIREn Resource Description Lookup DEST INAT IO N MULTIMEDIA PRESENTATIONExtensible DYNAMIC Real-time AUTOMATIC PLAYBACK
- 45. Slide Presenter TopicToTopic Topic Topic Youtube GoogleMaps GoogleImage … … Outroduction Text-to- speech Pathfinding Title Slide Composite User HTML5 & JS WEB Application = Slidegenerator Introduction
- 46. AGENDA1 CONCEPT 3 PATH NARRATION 2 PATHFINDING 4 DEMO
- 47. www.Everythingisconnected.be Linked Data made tangible high performance pathfinding in Large datasets Real-time multimedia narration of Paths Miel Vander Sande – miel.vandersande@ugent.be
- 48. A'ribu,on • Photo slide #3: www.sos.ca.gov • Photo slide #6: h'p://www.flickr.com/photos/joebenjamin/ • Photo slide #4: h'p://www.flickr.com/photos/ilri/ • Photo slide #7: h'p://www.flickr.com/photos/ andresmusta/ • Photo slide #11: h'p://www.flickr.com/photos/wtlphotos/ • Photo slide #12: h'p://www.flickr.com/photos/kristylopez/ • Photo slide #15: h'p://www.so'.net/ • Photo slide #21: h'p://www.flickr.com/photos/dr/ & h'p://www.flickr.com/photos/llimaorosa/