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Presentation given at OWLED 2011 (http://www.webont.org/owled/2011/), paper can be found here: http://www.knoesis.org/library/resource.php?id=1546
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Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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OWL Experiences and Directions (OWLED 2011)
Representation of Parsimonious Covering Theory
in OWL-DL
Cory Henson, Krishnaprasad Thirunarayan, Amit Sheth, Pascal Hitzler
Ohio Center of Excellence in Knowledge-enabled Computing (Kno.e.sis)
Wright State University, Dayton, Ohio, USA
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Find a set of entities (in the world) that
explain a given set of sensor observations
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Characteristics of a Solution
1. Handle incomplete information (graceful degradation)
2. Minimize explanations with additional information (anti-monotonic)
3. Reason over data on the Web (i.e., RDF on LOD)
4. Scalable (tractable)
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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http://linkedsensordata.com
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Semantic Sensor Network (SSN) Ontology
http://www.w3.org/2005/Incubator/ssn/wiki/
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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minimizeexplanations
degrade gracefullytractable
Parsimonious Covering Theory (PCT)
Web OntologyLanguage (OWL)
Convert PCT to OWL
Web reasoning
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Parsimonious Covering Theory
• Goal is to account for observed symptoms with plausible explanatory hypotheses (abductive logic)
• Driven by background knowledge modeled as a bipartite graph causally linking disorders to manifestations
Yun Peng, James A. Reggia, "Abductive Inference Models for Diagnostic Problem-Solving"
m1
m2
m3
d1
d2
d3m4
disorder manifestationcauses
explanationobservations
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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PCT Parsimonious Cover
• coverage: an explanation is a cover if, for each observation, there is a causal relation from a disorder contained in the explanation to the observation
• parsimony: an explanation is parsimonious, or best, if it contains only a single disorder (single disorder assumption)
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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Given
PCT problem P is a 4-tuple D, M, C, Γ⟨ ⟩
• D is a finite set of disorders• M is a finite set of manifestations• C is the causation function [C : D Powerset(M)]⟶• Γ is the set of observations [Γ M ]⊆
Δ is a valid explanation (i.e., is a parsimonious cover)
Goal
Translate P into OWL, o(P), such that o(P) ⊧ Δ
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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headache
extreme exhaustion
severe ache and pain
stuffy nose
sneezing
sore throat
severe cough
mild ache and pain
mild cough
flu
cold
fever
disorder manifestationcauses
PCT Background
Knowledge in OWL
disorders (D)
for all d ∈ D, write d rdf:type Disorderex: flu rdf:type Disorder
cold rdf:type Disorder
manifestations (M)
for all m ∈ M, write m rdf:type Manifestation
ex: fever rdf:type Manifestationheadache rdf:type Manifestation …
causes relations (C)
for all (d, m) ∈ C, write d causes mex: flu causes fever
flu causes headache …
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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PCT Observations and
Explanations in OWL
observations (Γ)
for mi ∈ Γ, i =1 … n, write
Explanation owl:equivalentClasscauses value m1 and … causes value mn
ex: Explanation owl:equivalentClasscauses value sneezing andcauses value sore-throat causes value mild-cough
explanation (Δ)
Δ rdf:type Explanation, is deduced
ex: cold rdf:type Explanationflu rdf:type Explanation
and
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
Ohio Center of Excellence on Knowledge-Enabled Computing (Kno.e.sis)
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thank you, and please visit us at
http://semantic-sensor-web.com
Knoesis – Ohio Center of Excellence in Knowledge-enabled ComputingWright State University, Dayton, Ohio, USA
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