Transcript Knowledge Composition Tool (ppt source)

.
Tools For Resolving Heterogeneity
in Ontologies
SKC Project
Computer Science Department
Stanford University
Gio Wiederhold, PI
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Gio Wiederhold SKC RKF 1
Problem Addressed by SKC
Ontologies come from many autonomous sources
• Differing viewpoints
(by source)
– differing coverage
vehicles (DMV, AIA)
– differing granularity
trucks (shipper, manuf.)
– differing terms for similar items
{ lorry, truck }
– same terms for dissimilar items trunk(luggage, car)
• Created by focused groups
– high quality
used in commerce
– ongoing maintenance
annual models
• Poor precision when merged
ok for web browsing ,
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poor for business
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Domains and Consistency
.
• a domain will contain many objects
• the object configuration is consistent
• within a domain all terms are consistent &
• relationships among objects are consistent
Domain Ontology
• context is implicit
No committee is needed
to forge compromises *
within a domain
 Compromises hide valuable details
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Heterogeneity among Domains
If interoperation involves distinct
domains mismatch ensues
• Autonomy conflicts with consistency,
– Local Needs have Priority,
– Outside uses are a Byproduct
Heterogeneity must be addressed
• Platform and Operating Systems 4 4
• Representation and Access Conventions 4
• Naming and Ontology :
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SKC Objective
Provide for Maintainable Ontologies
• devolve maintenance onto many
domain-specific experts / authorities
• provide an algebra to compute
composed ontologies that are
limited to their articulation terms
SKC
• enable interpretation within the
source contexts
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An Ontology Algebra
A knowledge-based algebra for ontologies
Intersection
Union
Difference
create a subset ontology
keep sharable entries
create a joint ontology
merge entries
create a distinct ontology
remove shared entries
The Articulation Ontology (AO) consists of
matching rules that link domain ontologies
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Sample Operation: INTERSECTION
Articulation
Source Domain 1:
Owned and maintained
by Store
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Result contains
shared terms,
useful for purchasing
Source Domain 2:
Owned and maintained
by Factory
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Tools to create articulations
Graph matcher
for
Articulationcreating
Expert
Transport
ontology
Vehicle
ontology
Suggestions
for articulations
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continue from initial point
Also suggest similar terms
for further articulation:
• by spelling similarity,
• by graph position
• by term match repository
Expert response:
1. Okay
2. False
3. Irrelevant
to this articulation
All results are recorded
Okay’s are converted into articulation rules
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Candidate Match Repository
Term linkages automatically extracted from 1912 Webster’s dictionary *
* free, other sources
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Based on processing
headwords  definitions
using algebra primitives
being processed.
Notice presence
of 2 domains:
chemistry, transport
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Using the Match Repository
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Using the Match Repository
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Rules for Real-Time Data
if [base_station.receiving] = true
then satellite_data = [base_station]
satellite_data.timestamp = now
if [satellite_data.age] < 24 hours
or [radio_jamming.level] > 30%
then recon_data = [satellite_data]
except when [flight_data.age] < 1 hour
or [rain_sensor.daytotal] > 1 inch
then recon_data = [flight_data]
assert [recon_data]
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INTERSECTION support
Articulation ontology
Terms useful
for purchasing
Matching
rules that use
terms from the
2 source domains
Store
Ontology
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Factory
Ontology
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Other Basic Operations
DIFFERENCE: material
fully under local control
UNION: merging
entire ontologies
Articulation
ontology
typically prior
intersections
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Features of an algebra
Operations can be composed
Operations can be rearranged
Alternate arrangements can be evaluated
Optimization is enabled
The record of past operations can be
kept and reused when sources change
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Knowledge Composition
Composed knowledge for
applications using A,B,C,E
Articulation
knowledge
Legend:
U
U
for
(A B) U
(B C) U
(C E)
Articulation
knowledge
(C E)
U
U : union
U
: intersection
Knowledge
resource
E
U
Knowledge
resource
A
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U
(B
C)
Knowledge
resource
B
Knowledge
resource
C
(C
U
U
Articulation
knowledge
for (A B)
D)
Knowledge
resource
D
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Primitive Operations
Model and Instance
Unary
• Summarize -- abstract
• Glossarize - list terms
• Filter - reduce instances
• Extract - move into context
Binary
• Match - data corrobaration
• Difference - distance measure
• Intersect - use of articulation
• Union - search broadening
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Constructors
• create object
• create set
Connectors
• match object
• match set
Editors
• insert value
• edit value
• move value
• delete value
Converters
• object - value
• object indirection
• reference indirection
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Exploiting the result
Result has links
to source
.
Avoid n2 problem of interpreter
mapping [Swartout HPKB year 1]
Processing & query
evaluation is best
performed within
Source Domains
& by their engines
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Sample Processing in HPKB
• What is the most recent year
an OPEC member nation was
on the UN security council?
– Related to DARPA HPKB
Challenge Problem
– SKC resolves 3 Sources
» CIA Factbook ‘96 (nation)
» OPEC (members, dates)
» UN (SC members, years)
– SKC obtains the
Correct Answer
» 1996 (Indonesia)
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– Problems resolved by SKC
* Factbook has out of date
OPEC & UN SC lists
• Indonesia not listed
• Gabon (left OPEC 1994)
* different country names
• Gambia => The Gambia
* historical country names
• Yugoslavia
» UN lists future security
council members
• Gabon 1999
» intent of original question
• Temporal variants
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Domain Specialization
.
• Knowledge Acquisition (20% effort) &
• Knowledge Maintenance (80% effort *)
to be performed
• Domain specialists
• Professional organizations
• Field teams
of modest size
automously
maintainable
Empowerment
* based on experience with software
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