Evaluation of Term-based Queries using Possibilistic Ontologies

Loiseau, Yannick; Prade, Henri

doi:10.1007/11370697_8

Cited by 3 publications

(3 citation statements)

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“…It is nevertheless questionable whether crisp ontologies can always find a consensus in the scientific community for modelling such complex and fuzzy objects like cities, informal settlements, local ecosystems, functional regions, cultural areas, etc. Within the artificial intelligence community, Bobilo andStraccia (2011), Costa et al (2008), Ding and Peng (2004) and Loiseau et al (2006) propose uncertainty-based ontologies for dealing with uncertain object definitions. Fuzzy logics, Bayesian probabilities and possibility theories are the proposed methods to enrich traditional formal ontologies.…”

Section: Uncertainty In Geographic Definitionsmentioning

confidence: 99%

Questions of uncertainty in geography

Fusco¹,

Caglioni²,

Emsellem³

et al. 2017

Environ Plan A

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International audienceThe concept of uncertainty has fostered in the last decade’s fundamental and applied research in different disciplinary fields. Couclelis (2003) clearly demonstrated the pervasiveness of uncertainty in the production process of geographical knowledge. The paper shares this epistemological point of view. Pragmatically, its goal is to show how questions of uncertainty arise in the praxis of geographic research. It suggests that scientific work can be enriched, and not hindered, by addressing uncertainty in knowledge. The paper discusses eight domains within the activity of the geographer, where questions of uncertainty arise: geographic information, geographic definitions, the explanation of geographic phenomena, the complexity of spatial systems, geosimulation, the representation of spatial knowledge, subjectivity in spatial phenomena, and planning. Within each domain uncertainty issues are identified as well as their possible interrelations

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Section: Uncertainty In Geographic Definitionsmentioning

confidence: 99%

Questions of uncertainty in geography

Fusco¹,

Caglioni²,

Emsellem³

et al. 2017

Environ Plan A

View full text Add to dashboard Cite

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“…Comment citer ce document : Thomopoulos, R., Buche studies about possibilistic ontologies [7], each term of an ontology is considered as a linguistic label and has an associated fuzzy description. Fuzzy pattern matching between different ontologies is then computed using these fuzzy descriptions.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Sets Defined on a Hierarchical Domain

Thomopoulos¹,

Buche²,

Haemmerlé

2006

IEEE Trans. Knowl. Data Eng.

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Abstract-This paper presents a new type of fuzzy sets, called "Hierarchical Fuzzy Sets", that apply when the considered domain of values is not "flat", but contains values that are more specific than others according to the "kind of" relation. We study the properties of such fuzzy sets, that can be defined in a short way on a part of the hierarchy, or exhaustively (by their "closure") on the whole hierarchy. We show that hierarchical fuzzy sets form equivalence classes in regard to their closures and that each class has a particular representative called "minimal fuzzy set". We propose a use of this minimal fuzzy set for query enlargement purposes and thus present a methodology for hierarchical fuzzy set generalization. We finally present an experimental evaluation of the theoretical results described in the paper, in a practical application.

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“…We can distinguish, especially in recent research:  the use of linguistic labels in ontologies. In studies about possibilistic ontologies (Loiseau et al, 2005), each term of an ontology is considered as a linguistic label and has an associated fuzzy description. Fuzzy pattern matching between different ontologies is then computed using these fuzzy descriptions.…”

Section: Introducing Fuzziness In Hierarchiesmentioning

confidence: 99%

Hierarchical Fuzzy Sets to Query Possibilistic Databases

Thomopoulos

Buche

Haemmerlé

Handbook of Research on Fuzzy Information Processing in Databases

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Within the framework of flexible querying of possibilistic databases, based on the fuzzy set theory, this chapter focuses on the case where the vocabulary used both in the querying language and in the data is hierarchically organized, which occurs in systems that use ontologies. We give an overview of previous works concerning two issues: firstly, flexible querying of imprecise data in the relational model; secondly, the introduction of fuzziness in hierarchies. Concerning the latter point, we develop an aspect where there is a lack of study in current literature: fuzzy sets whose definition domains are hierarchies. Hence we propose the concept of hierarchical fuzzy set and present its properties. We present its application in the MIEL flexible querying system, for the querying of two imprecise relational databases, including user interfaces and experimental results.

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Evaluation of Term-based Queries using Possibilistic Ontologies

Cited by 3 publications

References 0 publications

Questions of uncertainty in geography

Questions of uncertainty in geography

Fuzzy Sets Defined on a Hierarchical Domain

Hierarchical Fuzzy Sets to Query Possibilistic Databases

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