Recognition introduction-dec-2010
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Recognition introduction-dec-2010

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    Recognition introduction-dec-2010 Recognition introduction-dec-2010 Presentation Transcript

    • RECOGNITION: Relevance and  RECOGNITION: Relevance and Cognition for Self‐Awareness in  a Content‐Centric InternetStuart M. Allen, Franco Bagnoli, Gualtiero Colombo,  gMarco Conti, Jon Crowcroft, Chris Jones, Pietro Liò,  Refik Molva, Melek Onen, Andrea Passarella, Ioannis Stavrakakis, Roger M. Whitaker, Eiko Yoneki k k h k k k RECOGNITION overview 1 December 2010
    • Motivation: Technological Trends Motivation: Technological Trends• Participatory generation of content p yg – Prosumers, diversity, expanding edges – Long tail, swamping, scale! • Content in the environment – Linkage of the physical and virtual worlds – Embedding content and knowledge• Acquiring knowledge through social  q g g g mechanisms – Blogging, social networking,  recommendation, RSS feeds…• How content reaches users will  continue to change… ti t h RECOGNITION overview 2 December 2010
    • Self‐awareness to support  technological trends• Our Intention: Paradigm to support  ICT functions  ICT f ti – Enabling content centricity • Better fitting of users to content and vice Better fitting of users to content and vice  versa   – Synchronize content with human activity  and needs • Place, time, situation, relevance, context,  social search social search – Autonomic management • Of content, its acquisition and resource  utilization l RECOGNITION overview 3 December 2010
    • Human Awareness BehavioursHuman Awareness Behaviours• A Approach: Capture & exploit key  h C & l i k behaviours of the most intelligent  living species living species – Human capability is phenomenal in  navigating complex & diverse stimuli navigating complex & diverse stimuli – Filter & suppress information in “noisy”  situations with ambient stimuli – Extract knowledge in presence of  uncertainty –EExercise rapid value judgment for  i id l j d tf prioritisation – Engage a social context and multi‐scale Engage a social context and multi scale  learning RECOGNITION overview 4 December 2010
    • Human Awareness Behaviours Human Awareness Behaviours Cognitive psychological basis For awareness and understanding  Defining key principles for exploitation by  technology components   technology components Embedding these principles for  self‐awareness in autonomic content  acquisition in pervasive  environmentsPotential change in behaviour due to  self–awareness in ICT RECOGNITION overview 5 December 2010
    • Overview of Structure Overview of Structure UNIFI LEADCU LEAD CNR LEAD NKUA LEAD UCAM LEAD RECOGNITION overview 6 December 2010
    • Providing Autonomic Content  Management• Th Through Recognition “Nodes”, content becomes as self‐ hR iti “N d ” t tb lf aware as devices• Allow individuals to gain content that they didn’t know  g y they wanted…• Geo‐Informatics: space, place, time… – C t t l Content placement & retrieval based on situation and location t& t i lb d it ti d l ti• Storage and forwarding decisions based on relevance from: – Social context Social context – Location & environment• Trust & security management – Uncertainty & belief RECOGNITION overview 7 December 2010
    • Interdisciplinary Dimensions Interdisciplinary Dimensions– Complex systems– Artificial intelligence– Geo‐informatics– Cognitive psychology Cognitive psychology– Information retrieval– Communication systems– Security, trust RECOGNITION overview 8 December 2010
    • Key Questions… Key Questions• Psychology – What key concepts should be develop/include? y p p/ – Can these be used in different parts of the project?• Scenarios – What contemporary areas of “social computing” are  key to prioritise? key to prioritise? – What would have the biggest impact? – Are there demo’s that could be developed?• Other questions……. RECOGNITION overview 9 December 2010
    • Proposal:  Psychology areas Proposal: “Psychology” areas• Recognition, Probabilistic Mental Models,  b bl l d l Heuristics  –HHuman characteristics for agents h t i ti f t – Decision making under bounded rationality • Social Learning Social Learning – Observing, retaining, learning, replicating (mimicking)• Spatial Cognition Spatial Cognition – Space, place, context• Belief Desire and Intention models Belief, Desire and Intention models – Pulling from different areas of psychology but not fully  grounded RECOGNITION overview 10 December 2010
    • 1 ‐ Relevance Theory 1 Relevance Theory• Sperber and Wilson p – Non‐coding model of communication – Inferential model taking into account  context via “utterances” – provide "cognitive effects" worthy of the  processing effort required to find the  processing effort required to find the meaning • The speaker purposefully gives a clue to the  hearer • The hearer infers the intention from the clue  and the context‐mediated information. The  hearer must interpret the clue, taking into  account the context, and surmise what the  speaker intended to communicate. RECOGNITION overview 11 December 2010
    • 2‐ Judgment & Decision Making  2 Judgment & Decision Making• Work of Daniel Goldstein et al  – Heuristics that make us smart… • “Take the best” heuristic • Recognition heuristic – Bounded rationality Bounded rationality • Limited direct knowledge/partial info • Fast inference has to be made Fast inference has to be made… RECOGNITION overview 12 December 2010
    • 2‐ Judgment & Decision Making  2 Judgment & Decision Making• Take the best heuristic Take the best heuristic  – judgment based on multiple criteria • the criteria are tried one at a time the criteria are tried one at a time  according to their “cue validity” • high cue validity for a given feature  g y g means that the feature or attribute is  more diagnostic of the class membership  than a feature with low cue validity than a feature with low cue validity – a decision is made based on the first  discriminating criterion  discriminating criterion • the heuristic did well at making accurate  inferences in real world environments  RECOGNITION overview 13 December 2010
    • 2‐ Judgment & Decision Making  2 Judgment & Decision Making• Recognition heuristic Recognition heuristic  – If one of two objects is recognized and  the other is not, then infer that the  the other is not then infer that the recognized object has the higher value  with respect to the criterion. p – Sensitive to the criterion • Methodology for “cue validity” Methodology for  cue validity – Less‐is‐more effect  • Limited information does not impede Limited information does not impede  performance (to the contrary!) RECOGNITION overview 14 December 2010
    • 3‐ Spatial Cognition 3 Spatial Cognition• Human understanding and meaning for Human understanding and meaning for  ill‐defined but commonly used spatial  terms  • South east… • South Wales • Central london • Use of these in geo‐spatial content  g p so that it can become self‐aware  RECOGNITION overview 15 December 2010
    • Key Questions… Key Questions• Psychology – What key concepts should be develop/include? y p p/ – Can these be used in different parts of the project?• Scenarios – What contemporary areas of “social computing” are  key to prioritise? key to prioritise? – What would have the biggest impact? – Are there demo’s that could be developed?• Other questions……. RECOGNITION overview 16 December 2010
    • Candidate Scenarios Candidate Scenarios• Information Retrieval & content provision – Human awareness when using search engine  interfaces – e.g., automatic cue detection & HCI• Self‐aware Multimedia and “Active” Data – MP3, other types of content – Self‐aware meta‐data for spatial problems Self‐aware meta‐data for spatial problems• Social Computing – Crowd sourcing, recommendation, filtering, micro‐ d i d i fil i i blogging, tagging RECOGNITION overview 17 December 2010
    • RECOGNITION: Relevance and  RECOGNITION: Relevance and Cognition for Self‐Awareness in  a Content‐Centric InternetStuart M. Allen, Franco Bagnoli, Gualtiero Colombo,  gMarco Conti, Jon Crowcroft, Chris Jones, Pietro Liò,  Refik Molva, Melek Onen, Andrea Passarella, Ioannis Stavrakakis, Roger M. Whitaker, Eiko Yoneki k k h k k k RECOGNITION overview 18 December 2010