Title: Boontawee Suntisrivaraporn, Guilin Qi, Qiu Ji, Peter Haase
1A Modularization-based Approach to Finding All
Justifications for OWL Entailments
- Boontawee Suntisrivaraporn, Guilin Qi, Qiu Ji,
Peter Haase
2An Example Ontology
Endocarditis v HeartDiease
3Content
- Description Logics
- Justification in Description Logics
- Finding Justifications
- Conclusion and Problems
4Content
- Description Logics
- Justification in Description Logics
- Finding Justifications
- Conclusion and Problems
5Description Logics
- Description Logics
- are mostly decidable fragments of first-order
predicate logic - provide logical underpinning of W3C standard OWL
- have different sub-languages with different
expressiveness - DLs have building blocks
- Concepts, roles, and individuals
- Example concept
HumanuFemale u (9married.Doctor) u
(8hasChild.(DoctortProfessor))
6Description Logics (Cont.)
- Knowledge Base KltT, Agt
- Terminological part(TBox)properties of concepts
and roles - Assertional part(ABox) properties of individuals
- Satisfiability of KB
9hasChild.Human v Human
8 x(9y(hasChild(x,y)Æ Human(y)) ! Human(x))
HappyMan(Bob), HasChild(Bob, Mary)
K is satisfiable , ?(K) is satisfiable
7Content
- Description Logics
- Justification in Description Logics
- Finding Justifications
- Conclusion and Problems
8What Is a Justification
- Date back to diagnosis in AI
- Is related to explanation
- Was originally proposed to debug inconsistency
- Is very important for ontology reasoning
9What Is a Justification
- Ontology Entailment
- Justification
10Example
11Example (Cont.)
?7
?6
Endocarditis v Disease
?2
?6
?11
Endocarditis v 9has-location.9part-of.HeartValve
?3
?11
?12
Endocarditis v 9has-location.9part-of.9part-of.Hea
rt
?9
?12
?13
Endocarditis v 9has-location.9has-location.9has-lo
cation.Heart
?13
?10
Endocarditis v9has-location.Heart
12Content
- Description Logics
- Justification in Description Logics
- Finding Justifications
- Conclusion and Problems
13Compute One Justification
14Relevance-based strategy
15Finding All Justifications
16Finding All Justifications
17Hitting Set Three Algorithm
18Challenging Problems
- Fine-grained justifications
- irrelevant parts of an axiom
- Example BvCuD, DvE² BvE
- Scalability
- NP-hard for all DLs
- Existing algorithms do not scale
19Modularization-based Strategy
Apply Hitting Set Three algorithm to the module
20Experiments
21Experiments (Cont.)
22Experiments (Cont.)
Module size
of Just.
Just. Size (AVG)
23Content
- Description Logics
- Justification in Description Logics
- Finding Justifications
- Conclusion and Problems
24Conclusion
- Finding justifications is an important reasoning
task in ontology engineering - Current approaches to find justifications
- Expand Hitting Set Tree by computing one
justification - There are a couple of strategies to compute one
justification - Scalability of the current approach is a problem
- A modularization-based approach is proposed to
deal with this problem - Applications understanding undesirable
subsumption, debugging and repair mapping
25Problems
- Scalability
- Possible solutions approximation, partitioning,
information retrieval, abductive reasoning - There are potentially exponential justifications
- Compute only justifications relevant to some
degree - User-friendly justifications
- Natural language generation
26Thank You