Measuring Similarity in Description Logics using Refinement Operators
Publication Type:
Conference PaperSource:
Case-Based Reasoning Research and Development: 19th International Conference on Case-Based Reasoning (ICCBR'11), Volume 6880, p.289 - 303 (2011)Keywords:
CBR; Similarity; Description Logics; Refinement GraphAbstract:
Similarity assessment is a key operation in many artificial intelligence fields, such as case-based reasoning, instance-based learning, ontology matching, clustering, etc. This paper presents a novel measure for assessing similarity between individuals represented using Description Logic (DL). We will show how the ideas of {\em refinement operators} and {\em refinement graph}, originally introduced for inductive logic programming, can be used for assessing similarity in DL and also for abstracting away from the specific DL being used. Specifically, similarity of two individuals is assessed by first computing their {\em most specific concepts}, then the {\em least common subsumer} of these two concepts, and finally measuring their distances in the refinement graph
PDFFile:
Similarity for attribute-value representations in Fuzzy Description Logics
Publication Type:
Conference PaperSource:
Artificial Intelligence Research and Development, CCIA'10, IOS Press, p.269-278 (2010)Keywords:
Similarity; Fuzzy; Description LogicsAbstract:
In this paper we explore the possibility of introducing the
equality symbol in the languages of Fuzzy Description Logics (FDLs)
interpreted as a similarity relation. The goal is twofold: dealing with
attribute-value representations at the domain objects level, and integrating
the treatment of similarities inside the description languages and
their corresponding knowledge bases.
From Classical Description Logic to n-graded Fuzzy Description logics
Fuzzy Description Logics and t-norm based Fuzzy Logics
Publication Type:
Journal ArticleSource:
International Journal of Approximate reasoning, Elsevier, Volume 51, Issue 6, p.632 -- 655 (2010)Keywords:
Description Logics; Fuzzy Description Logics; Many-valued Logics; Propositional and Predicate t-norm based Fuzzy Logics; Truth-constantsReceived 22 May 2009Abstract:
Description Logics (DLs) are knowledge representation languages built on the basis of classical logic. DLs allow the creation of knowledge bases and provide ways to reason on the contents of these bases. Fuzzy Description Logics (FDLs) are natural extensions of DLs for
dealing with vague concepts, commonly present in real applications. Ha?jek proposed to
deal with FDLs taking as basis t-norm based fuzzy logics with the aim of enriching the
expressive possibilities in FDLs and to capitalize on recent developments in the field of
Mathematical Fuzzy Logic. From this perspective we define a family of description lan-
guages, denoted by
ALC
On Triangular Norm based Fuzzy Description Logics
Publication Type:
Conference PaperSource:
IFSA-EUSFLAT, Calouste Gulbekian Foundation, 20-24 July 2009. Lisbon, Portugal, p.891-896 (2009)ISBN:
978-989-95079-6-8Keywords:
Description Logics; Fuzzy Description Logics; t-norm based fuzzy logics; Truth-constants; Involutive negationAbstract:
Description Logics (DLs) are knowledge representation languages useful to represent concepts and roles. Fuzzy Description Logics (FDLs) incorporate both vague concepts and vague roles
modeling them as fuzzy sets and fuzzy relations respectively.
In the present paper, following ideas from H\'ajek, we propose the use of t-norm based (fuzzy) logics with truth constants in the language as logics underlying the fuzzy description language. We introduce the
languages ALC_L*(Al[S]) and ALC_L*_(Al[S]) as an adequate syntactical counterpart of some semantic calculi given in different works dealing with FDLs.
