Upload
nenet
View
33
Download
3
Tags:
Embed Size (px)
DESCRIPTION
Internet Reasoning Service: Progress Report. Wenjin Lu and Enrico Motta Knowledge Media Institute Monica Crubézy Stanford Medical Informatics. IRS: What it is?. Web-based tool to support reuse of reasoning services Different levels of support Manual browsing/configuration - PowerPoint PPT Presentation
Citation preview
Internet Reasoning Service:Progress Report
Wenjin Lu and Enrico MottaKnowledge Media Institute
Monica CrubézyStanford Medical Informatics
IRS: What it is?
• Web-based tool to support reuse of reasoning services
• Different levels of support– Manual browsing/configuration– Intelligent Assistant
• In the long term: broker-mediated service
Generic Classification Task
• Input roles– Candidate Solutions, Match Criterion, Solution
Criterion, Observables
• Precondition– Both observables and candidate solutions have to be
provided
• Goal– To find a solution from the candidate solutions which
is admissible with respect to the given observables, solution criterion and match criterion
3. Internet Reasoning Service
Task Selection
IRS provides a graphical and browsable description of each
generic task examples of pre-existing instantiated task models.
Can we do more?
Task Configuration (application inputs)
• Application inputs = case-independent ones• Instantiate by
– Mapping to domain model• Solution Space -> Hierarchy of apple types
– Directly filling task roles• Defining a new match criterion encoding constraint
according to the relevant task ontology
– Selecting from available options• choosing existing match criterion
Task Configuration (Case inputs)
• No need to fill case inputs at this stage• Still, mappings may be required
– Observables features -> apple properties
Task Model Verification
Task Model Verification = Checking task assumptions (only if they do not rely on case-specific inputs).
Can task assumptions rely on case-specific inputs?
PSM Selection
• Through a direct link between a PSM and a task. – e.g., in OCML PSMs are linked to the tasks that they can
solve by a special slot “tackles-task”.
• Through an existing PSM-Task bridge• As the result of users’ choice among available PSMs.
– IRS will need to support the creation of relevant PSM-Task Bridge
• As the result of a competence matching process between the task and available PSMs. – Competence matching should generate appropriate PSM-
Task bridge
PSM Configuration
• Same as task configuration• Roles inherited from relevant task• PSM may define additional roles
– e.g., heuristic classifier introduces abstractors and refiners
PSM Verification
• Checking PSM Assumptions– again, only if no case-specific roles are involved
PSM Execution
Acquiring case-specific input from user. Checking precondition/assumptions Calling the PSM code with the mapped inputs.
Interpreter may be local or remote Displaying the progress of the PSM execution, at least
in a console window (that assumes that the code interpreter or the PSM code sends trace messages to the console).
Filling-in the domain outputs with the results of PSM execution (through mapping relations) and presenting those results to users.
Possible Platforms for IRS
• Specialized WebOnto Configuration– Unlikely– Nobody working on it
• Protégé– Based on pre-existing PSM Librarian plug-in– Monica working on it
• New Java/Lisp Tool– Java Applets interfaced with library sitting on Lisp
server– Wenjin working on it.
IRS in Protege
Additional Developments
• Classification library to be tried out in 2 domains– E-commerce
• user classification, product selection• configuration of ‘user basket’
– will use parametric design library
– Paleontology• Classification is everything in Paleontology• Complicated problem• No agreed hierarchy/classification rules
– gaps in the models