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Mobile social search
 

Mobile social search

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My presentation at Search Computing on a topic that I think is going to be quite popular soon.

My presentation at Search Computing on a topic that I think is going to be quite popular soon.

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Mobile social search Mobile social search Presentation Transcript

  •  9/25/12   1  
  • An  Elephant  and  Six  Blind  Men  
  • An  Elephant  is  NOT  •  Wall  •  Rope  •  Snake  •  Spear  •  Tree  •  Fan  
  • An  Elephant  is  …   an  Elephant  
  • Mobile  Social  Search  (MSS)   is  NOT  Mobile     is  NOT  Social     is  NOT  Search   Is  Mobile  Social  Search  
  • Changing  Times  in  Search  Mobile  Social  Search:    Search  ‘inside’  problem  solving  in  real  ;me.   Problem  Solving       Search    
  • MSS:  A  Problem  of  Riches   When  we  were  (data)  poor  –   we  searched.     Now  that  we  are  (data)  rich  –   we  need  mobile  social   search.    
  • SearchConnecting
  • Then Now
  • Then Now
  • •  What  is  an  Italian  Restaurant?   –  List  Italian  Restaurants  in  Brussels.  •  Show  me  Italian  Restaurants?   –  Use  Yelp  (or  any  other  social  approach)  and  distance   from  me  to  rank  them.  •  Where  should  I  go  to  eat  Italian  food  NOW?   –  Consider  Tme  taken,  current  ambiance,  and  quality   of  food  into  consideraTon.  
  • •  What  are  symptoms  of  Swine  Flu?  •  Is  there  a  major  Swine  Flu  outbreak  in  my  area?  •  You  are  likely  to  be  very  sick  with  extreme  case   of  Swine  Flu  soon,  your  doctor  is  ready  with  the   set  up.  
  • Social  Networks    Connecting People
  • Social  Life  Networks   Connecting Information     People Aggregation Situation Alerts and Detection CompositionAnd Queries Resources9/25/12   14  
  • Concept  recogni;on  from  data   Heterogeneous  Media   Heterogeneous  Media   LocaTon   Scenes   Single  Media   Environm Trajectories   SituaTons   aware   ents   K   3.4   Single  Media   LocaTon   Visual   Real  world   Visual   360  K   11.4K   AcTviTes   unaware   Objects   Objects   Events   StaTc   Dynamic   SPACE   TIME   15  
  • Proprietary  and  ConfidenTal,  Not  For  9/25/12   16   DistribuTon  
  • •  SituaTon:  An  acTonable  abstracTon  of   observed  spaTo-­‐temporal  characterisTcs.  •  Allow  users  to  define  their  own  spaTo-­‐ temporal  features  and  create  the  situaTon   detecTon  filters.    9/25/12   17  
  • Swine  flu:  Situa;on  Segmenta;on   into  ‘high’  and  ‘low  ’ac;vity  zones.   Proprietary  and  ConfidenTal,  Not  For  9/25/12   18   DistribuTon  
  • (a) Pollen levels (Source: Visual) (b) Census data (Source: text file) (c) Reports on ‘Hurricanes’ (source: Twitter stream)  d) Cloud cover (Source: Satellite imagery) (e) Predicted hurricane path (source: KML) (f) Open shelters coverage(Source: KML)   Representa;on  for  different  data  sources  into  a  common   spa;o-­‐temporal  format.    
  • Level  0:  Raw  data  streams    e.g.  tweets,  cameras,  traffic,  weather,  …   …   Level  1:  Unified   representaTon   ProperTes (STT  Data)   STT  Stream   Level  2:   AggregaTon   ProperTes Emage   (Emage)     Level  3:   Symbolic  rep.   ProperTes SituaTon   (SituaTons)  
  • Billions  of  data  sources.    Selec;ng  and  combining  appropriate  sources  to  detect  situa;ons.    Interac;ons  with  different  types  of  Users    Decision  Makers                            Individuals     9/25/12   21  
  • Front  End  GUI New New E-­‐mage Alert Data Query Stream Request Source Back  End  Controller E-­‐mage  Stream Personalized   Registered Stream  Query  Processor Queries Alert  Unit E-­‐mage  Stream User  Info Registered Data Data  Ingestor Raw  Data Storage Sources API  Calls Raw  Spatial   Data  Stream Data  Cloud9/25/12   22  
  • 9/25/12   23  
  • S.  No   Operator   Input   Output  1   Selection  σ   Temporal     Temporal     E-­‐mage  Set   E-­‐mage  Set  2   Arithmetic    &   K*Temporal  E-­‐mage   Temporal  E-­‐mage  Set   Logical⊕   Set  3   Aggregation  α   Temporal  E-­‐mage  set   Temporal  E-­‐mage  Set  4   Grouping  γ   Temporal  E-­‐mage  Set   Temporal  E-­‐mage  Set  5   Characterization  :   • Spatial  φ   • Temporal  E-­‐mage  Set   • Temporal  Pixel  Set   • Temporal  τ   • Temporal  Pixel  Set   • Temporal  Pixel  Set  6   Pattern  Matching  ψ   • Spatial  φ   • Temporal  E-­‐mage  Set   • Temporal  Pixel  Set   • Temporal  τ   • Temporal  Pixel  Set   • Temporal  Pixel  Set   9/25/12   24  
  • Personal  SituaTon   Proprietary  and  ConfidenTal,  Not  For  9/25/12   25   DistribuTon  
  • Macro  situa;on   Alert  Level=High   Date=12/09/10   Micro  event   Situa;onal  controller   Control  Ac;on   e.g.  “Arrgggh,  I     “Please  visit  have  a  sore  throat”   • Goal     nearest  CDC   (Loc=New  York,   • Macro  SituaTon     center  at  4th  St   Date=12/09/10)   • Rules   immediately”   Level  1  personal  threat  +  Level  3  Macro  threat  -­‐>  Immediate  ac;on     9/25/12   26  
  • Planetary   1)  Macro          scale  sensing   situaTon  Social  sensors  Device  sensors  Macro  sensors   2)  Personalized     situaTon     Personal     context     Personal  life  streams         Profile/     Preferences   e.g.  High  Flu  risk   3)  Recommend                     AcTons       Available   resources   Resource  data  
  • Classify (Flood level - Shelter Flood Shelter) Twitter Flood Level Shelter9/25/12   28  
  • Taking  personalized  acTons  9/25/12   29  
  • •  Was  for  Archived  data  and  mostly  for   researchers  (using  Desktop).  •  Currently:  Mobile  clients,  Local  data,  and   Social  Graph  (SoMoLo).  •  Immediate  Future:  SituaTons  from  Real  Time   data  and  RecommendaTons.  •  Future:  PredicTve  control  of  emerging   situaTons.  
  • Thanks  for  your  Tme  and  alenTon.   For  quesTons:  jain@ics.uci.edu  
  • Applica;on  scenarios   ¨  Business  decision  making:  Demand-­‐supply  analysis,   opening  a  new  store,  offer,…   ¨  Medical  :  Epidemic  monitoring,  Asthma,  polluTon   effect  miTgaTon   ¨  Disaster  relief:  (hurricane,  flood,  fire)  direcTng   people  to  appropriate  resources.   ¨  Traffic:  SuggesTng  best  routes      9/25/12   32