Lasso context-elicitation-framework- demo
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Transcript of Lasso context-elicitation-framework- demo
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www.lassoproject.org 1
KnowSe 2.0Context Elicitation Framework
Knowledge Management InstituteTU Graz
Contact: [email protected]
09.09.11
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Motivation
09.09.11
„Can we build an open source
framework which easily allows to
explore the current situation the user is
in?“
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Collect Data
• From different sources• Using various formats• Possible sources?– Sensors, crawlers, agents…– … which provide user related data
• For example:– Software sensors capturing user machine interactions
• e.g. mouse clicks, keyboard input
– Hardware sensors capturing physical conditions• e.g. heartbeat pulse, body temperature
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Infer Knowledge
• Apply context elicication methods• Depend on the application• Take low-level data and generate higher level
concepts• Use knowledge– For further analysis– For visualization
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Architectural Building Blocks
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Generic Framework Components
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Router
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• Concurrent request handling• Data is dispatched for
interested triplificators only• The others remove
themselves from the list of candidates
• As soon as data is available, data is read and dispatched
• One or more interested triplificators possible
• If none is interested connection request is not processed
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Generic Framework Components
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Registry
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• Lists the orchestra of available components
• E.g. router, triplificators, elicitation components etc.
• Registration is done upon system start
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Generic Framework Components
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Knowledge Base
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• Storage format: RDF• Behind the scenes: Sesame as
RDF Framework API• Modes of editing:
– Triples level– Model level
• Model level supports working with ontologies in an object oriented fashion
• Cross language compiler converts OWL into Java interfaces
• ModelEditor provides a simple way of accessing entities in the ontology
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Generic Framework Components
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Notificator
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• Behind the scenes: Equinox implementation of the OSGI Event Administration Service
• Provides sending/receiving notifications– Between bundles– Synchronous/asynchronous
fashion
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Application Dependend Framework Components
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Triplificator
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• Accept or deny requests from router– Multithreaded request
processing
• Converts data into triples• Transaction based storage
– If successful then commit– Otherwise rollback
• Broadcasts notifications via Notificator component
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Application Dependend Framework Components
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Elicitation Components
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• Get active upon notifications sent by other components
• Execute queries over the knowledge space– Sparql 1.1 Query Language
Support
• Generate higher level concepts
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Application Dependend Framework Components
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Sink
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• End of a processing chain• Transfer knowledge outside• “Refinder Sink”:
– Send information about resource similarity
– Via HTTP Post– Payload contains the RDF
graph
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Application Dependend Framework Components
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Orchestration
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• Application developer defines– Set of components – Initialization of components– Shutdown of components
• Each application has its own orchestration
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Wiki Visualization
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Wiki Visualization
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Wiki Visualization
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Wiki Visualization
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Wiki Visualization
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Future work
09.09.11
• Develop first release candidate
• Make it publicly available– as Open Source Software
• We want to provide a ready to use set of components– Including sensors– Visualizations– And more to come