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A Context Management Framework based on Wisdom of Crowds for Social Awareness applications Adrien JOLY PhD Candidate, supervisor: Prof. Pierre MARET, LaHC CIFRE: Alcatel-Lucent Bell Labs France + INSA-Lyon, LIRIS, UMR5205
Un cadre de Gestion de Contextes fondé sur l’Intelligence Collective pour améliorer l’efficacité des applications de Communication Sociale Adrien JOLY CIFRE: Alcatel-Lucent Bell Labs France + INSA-Lyon, LIRIS, UMR5205 Encadré par: Prof. Pierre MARET (LaHC), Johann Daigremont (ALBLF)
[object Object],[object Object],[object Object],[object Object],[object Object],Agenda of this presentation
Context  Approach  Framework  Evaluation  Conclusion   A PhD thesis in a moving industrial research lab ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Context  Approach  Framework  Evaluation  Conclusion   Introduction to social networks and information overload “ Aware” user ,[object Object],Activities / Status Updates / Contacts
Context  Approach  Framework  Evaluation  Conclusion   Introduction to social networks and information overload “ Aware” user Activities / Status Updates / Contacts ,[object Object],Information overload* * aka Cognitive Overflow Syndrome [Lahlou 1997]
Context  Approach  Framework  Evaluation  Conclusion   Introduction to social networks and information overload Filter “ Aware” user Activities / Status Updates / Contacts Needed ,[object Object],and productive
Context  Approach  Framework  Evaluation  Conclusion   Problem statement ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Context  Approach  Framework  Evaluation  Conclusion   State of the Art: Computer-Supported Collaborative Work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Context  Approach  Framework  Evaluation  Conclusion   State of the Art: content-based filtering ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Context  Approach  Framework  Evaluation  Conclusion   State of the Art: collaborative filtering ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Context  Approach  Framework  Evaluation  Conclusion   Proposal: context-aware filtering ,[object Object],[object Object],[object Object],[object Object],Java Dev I/O PHP Similar contexts Physical, virtual and social sensors Open set of context features User’s activity Recommend social updates
Context  Approach  Framework  Evaluation  Conclusion   Research issues ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Agenda of this presentation ,[object Object],[object Object],[object Object],[object Object],[object Object]
Context   Approach   Framework  Evaluation  Conclusion   Similarity of context, our hypothesis ,[object Object],[object Object],Hypothesis: I A  is relevant to  U X if  C A  is similar to  C X A A  = Travel in Asia U A  = Alice I A  = « Check out my amazing picture ! » A B  = Working Java U B  = Bob I B  = « What database should I use ? » A C  = Browsing map U C  = Christine I C  = « Looking for holiday locations… »
Context   Approach   Framework  Evaluation  Conclusion   Similarity of context, our hypothesis ,[object Object],[object Object],Hypothesis: I A  is relevant to  U X if  C A  is similar to  C X C A  = Travel, Asia C C  = Travel C B  = Java Dev. A A  = Travel in Asia U A  = Alice A B  = Working Java U B  = Bob I B  = « What database should I use ? » A C  = Browsing map U C  = Christine I C  = « Looking for holiday locations… » Similar context: travel No relevant match for this context I A  = « Check out my amazing picture ! »
Context   Approach   Framework  Evaluation  Conclusion   What is context ? ,[object Object],[object Object],[object Object],[object Object],Location Surrounding people Other sensors Communication history Web browsing history Document history
Context   Approach   Framework  Evaluation  Conclusion From physical context sensors to applications – usual approach Context sensors Applications Interpretation Acquisition db ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Context Management Framework
Context   Approach   Framework  Evaluation  Conclusion From physical,  virtual and social  context sensors to applications – our approach Context Management Framework Context sensors Social  Applications Interpretation Acquisition db ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Updates Paris  Notre-Dame  Café   Cloudy  Crowded Sitting  with:Pierre
Context   Approach   Framework  Evaluation  Conclusion   Our approach, the “Big Picture” ,[object Object],[object Object],[object Object],[object Object],[object Object],Mario is shopping near  Chatelet Mario: «  let’s grab a coffee at  SB !  » Alice  has just shared a photo [ view ] Lucie is listening to  Californication  [ i like this ] Kevin: «  new  McChicken  is great!  » Car incident  32 meters away Alice GPS Wifi McDonald’s restaurant Radio currently playing a song Christine
Agenda of this presentation ,[object Object],[object Object],[object Object],[object Object],[object Object]
Context   Approach  Framework   Evaluation  Conclusion   Context Aggregation and Filtering process Social updates Aggregator Sniffers Notifier Filter User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services
Context   Approach  Framework   Evaluation  Conclusion   Considering a first context dimension: browsing activity Social updates Aggregator Sniffers Notifier Filter User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services ,[object Object],[object Object]
Context   Approach  Framework   Evaluation  Conclusion   How to synthesize the contextual tag cloud from web browsing  ? The user opens a web page…
Context   Approach  Framework   Evaluation  Conclusion   How to synthesize the contextual tag cloud from web browsing  ? Low level and static author description Automatic content analysis Mining semantic concepts from content People-entered tags  (wisdom of crowds) 1) URL is sent to the  Context Aggregator 2) Content is analyzed by  enhancers  (including web services)
Context   Approach  Framework   Evaluation  Conclusion   Contextual Tag Clouds, vector space model and algebra Sample tag cloud  R : (normalized) ,[object Object],[object Object],[object Object],[object Object],0.1 0.1 0.3 0.5 « Discount » « Flight » « Asia » « Travel »
Context   Approach  Framework   Evaluation  Conclusion   Contextual Tag Clouds, extraction and enhancement functions ,[object Object],Title Keywords Description Parameters = 50 = 10 = 1
Context   Approach  Framework   Evaluation  Conclusion   Contextual Tag Clouds, extraction and enhancement functions ,[object Object],2.  Search Query ambient, awareness 3.  Resource Location video, all, alcatel-Lucent
Context   Approach  Framework   Evaluation  Conclusion   Contextual Tag Clouds, extraction and enhancement functions ,[object Object],w poster  = 11, w work  = 11, w gtd  = 10, w done  = 10, w inspiration  = 7, …
Context   Approach  Framework   Evaluation  Conclusion   Contextual Tag Clouds, extraction and enhancement functions ,[object Object],MIT, Tim Berners-Lee, …
Context   Approach  Framework   Evaluation  Conclusion   Context Aggregation and Filtering process –-  in the enterprise Social updates Aggregator Sniffers Notifier Filter User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services
Context   Approach  Framework   Evaluation  Conclusion   Implementation Firefox extension (Javascript) to track web browsing Windows daemon (C++) to track opened PDF documents Lightweight HTTP Server (Java) + 5 tag extractors (Java) incl. 2 web service wrappers Jetty-based HTTP Server (Java) DWR for server-push (Java) Off-line scripts (Java+shell) Firefox sidebar (HTML+Javascript) Mobile application (Java for android) Aggregator Sniffers Notifier Filter Social updates User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services
Context   Approach  Framework   Evaluation  Conclusion   Demonstration of the ECN prototype ,[object Object],[object Object]
Agenda of this presentation ,[object Object],[object Object],[object Object],[object Object],[object Object]
Context   Approach  Framework  Evaluation   Conclusion   Requirements and plan ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],(1 week) 2 personalized surveys per user Indexing as tags clouds & Matching  contexts
Context   Approach  Framework  Evaluation   Conclusion   From browsing activity to social matching Temporal indexing period = 10 mn. Common tags: JAVA, DEV Common tags: TRAVEL   Recommend u5’s social update to u1   Recommend u3’s social update to u7
Context   Approach  Framework  Evaluation   Conclusion   1. Relevance of social updates based on contextual similarity  Matching
Context   Approach  Framework  Evaluation   Conclusion   Survey #1 ,[object Object],1 2 3 4 1 2 3 4 ,[object Object]
Context   Approach  Framework  Evaluation   Conclusion   Survey #1 results 1/2 ,[object Object],[object Object]
Context   Approach  Framework  Evaluation   Conclusion   Survey #1 results 2/2 ,[object Object],Accuracy
Context   Approach  Framework  Evaluation   Conclusion   2. Relevance of social updates to the context of their posting
Context   Approach  Framework  Evaluation   Conclusion   Survey #2 ,[object Object],[object Object],[object Object],[object Object],[object Object]
Context   Approach  Framework  Evaluation   Conclusion   3. Differences between context from virtual and social sensors Combining virtual and social sensors: good compromise between quantity and quality of matches 280k Number of matches 40k 170k 130k 70k 10k Low precision matches High  precision matches
Agenda of this presentation ,[object Object],[object Object],[object Object],[object Object],[object Object]
Context   Approach  Framework  Evaluation  Conclusion   Conclusion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Context   Approach  Framework  Evaluation  Conclusion   Contributions and findings ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Context   Approach  Framework  Evaluation  Conclusion   Future work ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
www.alcatel-lucent.com Thank you for your attention! Merci pour votre attention !

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PhD Defense - A Context Management Framework based on Wisdom of Crowds for Social Awareness Applications

  • 1. A Context Management Framework based on Wisdom of Crowds for Social Awareness applications Adrien JOLY PhD Candidate, supervisor: Prof. Pierre MARET, LaHC CIFRE: Alcatel-Lucent Bell Labs France + INSA-Lyon, LIRIS, UMR5205
  • 2. Un cadre de Gestion de Contextes fondé sur l’Intelligence Collective pour améliorer l’efficacité des applications de Communication Sociale Adrien JOLY CIFRE: Alcatel-Lucent Bell Labs France + INSA-Lyon, LIRIS, UMR5205 Encadré par: Prof. Pierre MARET (LaHC), Johann Daigremont (ALBLF)
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  • 22. Context Approach Framework Evaluation Conclusion Context Aggregation and Filtering process Social updates Aggregator Sniffers Notifier Filter User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services
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  • 24. Context Approach Framework Evaluation Conclusion How to synthesize the contextual tag cloud from web browsing ? The user opens a web page…
  • 25. Context Approach Framework Evaluation Conclusion How to synthesize the contextual tag cloud from web browsing ? Low level and static author description Automatic content analysis Mining semantic concepts from content People-entered tags (wisdom of crowds) 1) URL is sent to the Context Aggregator 2) Content is analyzed by enhancers (including web services)
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  • 31. Context Approach Framework Evaluation Conclusion Context Aggregation and Filtering process –- in the enterprise Social updates Aggregator Sniffers Notifier Filter User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services
  • 32. Context Approach Framework Evaluation Conclusion Implementation Firefox extension (Javascript) to track web browsing Windows daemon (C++) to track opened PDF documents Lightweight HTTP Server (Java) + 5 tag extractors (Java) incl. 2 web service wrappers Jetty-based HTTP Server (Java) DWR for server-push (Java) Off-line scripts (Java+shell) Firefox sidebar (HTML+Javascript) Mobile application (Java for android) Aggregator Sniffers Notifier Filter Social updates User Actions and tags Contextual clouds Notifications Context Interfaces Abstraction and weighting Services
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  • 36. Context Approach Framework Evaluation Conclusion From browsing activity to social matching Temporal indexing period = 10 mn. Common tags: JAVA, DEV Common tags: TRAVEL  Recommend u5’s social update to u1  Recommend u3’s social update to u7
  • 37. Context Approach Framework Evaluation Conclusion 1. Relevance of social updates based on contextual similarity Matching
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  • 41. Context Approach Framework Evaluation Conclusion 2. Relevance of social updates to the context of their posting
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  • 43. Context Approach Framework Evaluation Conclusion 3. Differences between context from virtual and social sensors Combining virtual and social sensors: good compromise between quantity and quality of matches 280k Number of matches 40k 170k 130k 70k 10k Low precision matches High precision matches
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  • 48. www.alcatel-lucent.com Thank you for your attention! Merci pour votre attention !

Editor's Notes

  1. w t,d is the number of people p who annotated a given resource d using the term t .
  2. Counts the occurrences of each term that is semantically identified in the document’s content.