RECOGNITION: Relevance and RECOGNITION: Relevance and Cognition for Self‐Awareness in a Content‐Centric Internet Stuart M. Allen, Franco Bagnoli, Gualtiero Colombo, Marco Conti, Jon Crowcroft, Chris Jones, Pietro Liò, Refik Molva, Melek Onen, Andrea Passarella, kk h k k k Ioannis Stavrak akis, Roger M. Whitak er, Eik o Yoneki RECOGNITION overview December 2010 1
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RECOGNITION: Relevance andRECOGNITION: Relevance and Cognition for Self‐Awareness in
a Content‐Centric Internet
Stuart M. Allen, Franco Bagnoli, Gualtiero Colombo, gMarco Conti, Jon Crowcroft, Chris Jones, Pietro Liò,
Refik Molva, Melek Onen, Andrea Passarella, k k h k k kIoannis Stavrakakis, Roger M. Whitaker, Eiko Yoneki
RECOGNITION overviewDecember 2010
1
Motivation: Technological TrendsMotivation: Technological Trends• Participatory generation of contentp y g
– 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 gmechanisms– Blogging, social networking, recommendation, RSS feeds…
• How content reaches users will ti t h
RECOGNITION overviewDecember 2010
continue to change…2
Self‐awareness to support technological trends
• Our Intention: Paradigm to support ICT f tiICT functions – 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 searchsocial search
– Autonomic management• Of content, its acquisition and resource
lRECOGNITION overview
December 2010
utilization
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Human Awareness BehavioursHuman Awareness Behaviours
A h C & l i k• Approach: Capture & exploit key behaviours of the most intelligent living speciesliving species– Human capability is phenomenal in navigating complex & diverse stimulinavigating complex & diverse stimuli
– Filter & suppress information in “noisy” situations with ambient stimuli
– Extract knowledge in presence of uncertaintyE i id l j d t f– Exercise rapid value judgment for prioritisation
– Engage a social context and multi‐scale
RECOGNITION overviewDecember 2010
Engage a social context and multi scale learning
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Human Awareness BehavioursHuman Awareness Behaviours
Cognitive psychological basisFor awareness and understanding
Defining key principles for exploitation by technology componentstechnology components
Embedding these principles for self‐awareness in autonomic content acquisition in pervasive environments
Potential change in behaviour due to self–awareness in ICT
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Overview of StructureOverview of Structure
UNIFI LEADCU LEAD
CNR LEAD
NKUA LEAD UCAM LEADRECOGNITION overview
December 20106
NKUA LEAD UCAM LEAD
Providing Autonomic Content Management
Th h R iti “N d ” t t b lf• Through Recognition “Nodes”, content becomes as self‐aware as devices
• Allow individuals to gain content that they didn’t know g ythey wanted…
• Geo‐Informatics: space, place, time…C t t l t & t i l b d it ti d l ti– Content placement & retrieval based on situation and location
• Storage and forwarding decisions based on relevance from:– Social contextSocial context– Location & environment
• Belief Desire and Intention models• Belief, Desire and Intention models– Pulling from different areas of psychology but not fully grounded
RECOGNITION overviewDecember 2010
grounded
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1 Relevance Theory1 ‐ Relevance Theory• Sperber and Wilsonp
– Non‐coding model of communication– Inferential model taking into account context via “utterances”
– provide "cognitive effects" worthy of the processing effort required to find theprocessing 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.
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2 Judgment & Decision Making2‐ 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 overviewDecember 2010
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2 Judgment & Decision Making2‐ Judgment & Decision Making • Take the best heuristicTake 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 gmeans that the feature or attribute is more diagnostic of the class membership than a feature with low cue validitythan a feature with low cue validity
– a decision is made based on the first discriminating criteriondiscriminating criterion
• the heuristic did well at making accurate inferences in real world environments
– If one of two objects is recognized and the other is not then infer that thethe 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 impedeLimited information does not impede performance (to the contrary!)
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3 Spatial Cognition3‐ Spatial Cognition• Human understanding and meaning forHuman 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 pso that it can become self‐aware
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Key QuestionsKey Questions…
• Psychology– What key concepts should be develop/include?y p p/
– Can these be used in different parts of the project?
• Scenarios• 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…….
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Candidate ScenariosCandidate 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 problemsSelf‐aware meta‐data for spatial problems
• Social Computingd i d i fil i i– Crowd sourcing, recommendation, filtering, micro‐
blogging, tagging
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RECOGNITION: Relevance andRECOGNITION: Relevance and Cognition for Self‐Awareness in
a Content‐Centric Internet
Stuart M. Allen, Franco Bagnoli, Gualtiero Colombo, gMarco Conti, Jon Crowcroft, Chris Jones, Pietro Liò,
Refik Molva, Melek Onen, Andrea Passarella, k k h k k kIoannis Stavrakakis, Roger M. Whitaker, Eiko Yoneki