Imprecision and uncertainty in the UFO database model

Gyseghem, Nancy Van; Caluwe, Rita De

doi:10.1002/(sici)1097-4571(1998)49:3<236::aid-asi5>3.0.co;2-#

Cited by 21 publications

(5 citation statements)

References 12 publications

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“…Current efforts have been concentrated on fuzzy object-oriented databases and some related notions such as class, superclass/subclass, inheritance, etc. are extended [3,9,12,14,15,20]. More recently, the fuzzy object-relational databases were proposed [10] which combine both characters of fuzzy relational databases and fuzzy object-oriented databases.…”

Section: Introductionmentioning

confidence: 99%

Modeling fuzzy information in fuzzy extended entity-relationship model and fuzzy relational databases

2014

Journal of Intelligent &Amp; Fuzzy Systems

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Computer applications in non-traditional area have put requirement on conceptual data modeling. Some conceptual data models, being the tool of design databases, have been proposed. Information in real world application is often vague or ambiguous. Currently few researches have been done in modeling fuzziness in conceptual data model and design of fuzzy databases. In this paper, based on fuzzy set theory, different levels of fuzziness are introduced into the EER (enhanced/extended entity-relationship) model and the corresponding representations are given. The EER model is then extended to fuzzy EER model. The formal mapping of the fuzzy EER model into the fuzzy relational database schema is proposed in the paper.

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Section: Introductionmentioning

confidence: 99%

Modeling fuzzy information in fuzzy extended entity-relationship model and fuzzy relational databases

2014

Journal of Intelligent &Amp; Fuzzy Systems

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“…In the context of database models, fuzzy information modeling has been extensively investigated in [17,54,65,67,82]. To model uncertain data and complex-valued attributes as well as complex relationships among objects, which are required in many application domains [12,15,19,45,69,71,80,83], current efforts have concentrated on the fuzzy conceptual data models (e.g., fuzzy ER/EER data model [21,29,92,97] and fuzzy UML data model [51]) and the fuzzy object-oriented databases [16,24,30,34,56,91]. The conceptual design of fuzzy relational databases using the fuzzy ER data model and the fuzzy UML data model was investigated in [20,55], respectively, and the conceptual design of fuzzy object-oriented databases using the fuzzy EER data model and the fuzzy UML data model was presented in [53,58], respectively.…”

Section: Introductionmentioning

confidence: 99%

Extending engineering data model for web-based fuzzy information modeling

2013

ICA

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Being an information modeling language to support the STEP (Standard for Exchange of Product Model Data), EXPRESS has been developed to share and exchange product design, manufacturing and production data in product life cycle. Also being the de-facto standard of data representation and exchange over the Web, XML (eXtensible Markup Language) has been widely applied in Web-based engineering applications for product data exchange and share. It is essential to integrate EXPRESS data model and XML data model in engineering data modeling. EXPRESS-G is the graphical representation of EX-PRESS and can serve as the conceptual design of Web-based engineering data models. Fuzzy engineering information is inherent in many engineering activities. In order to explicitly represent and handle fuzzy engineering information, this paper introduces an extended EXPRESS-G data model for different kinds of fuzziness modeling. After presenting the formal descriptions and corresponding representations of the fuzzy EXPRESS-G data model, the paper investigates the formal transformation from the fuzzy EXPRESS-G data model to the fuzzy XML model. The formal transformation approaches proposed in the paper are demonstrated with engineering application examples.

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“…20 Most of the authors 17 ᎐ 19 have approached the management of both imprecision and uncertainty in the OODM. Van Gyseghem et al 19 and Tanaka et al 18 discuss the problem at both the theoretical and dynamic levels concerning the definition of methods. Another discussed issue is the incorporation of fuzziness and uncertainty in the instantiation of objects.…”

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confidence: 99%

“…Then, the membership degree of an object to a class is computed depending on the ''inclusion'' of the actual values of the attributes of the given object into the range of the attributes for that class. Van Gyseghem and De Caluwe 19 state that when the instantiation of an object is of a gradual nature it means that the behavior and structure of the object are not completely defined. Then, by introducing necessary and optional properties, they propose a mechanism based on thresholds to determine the properties of a class which are applicable to an object.…”

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confidence: 99%

“…Fuzziness is also considered at the level of class hierarchy. 19 ,21 ᎐ 23 Dubois et al 22 employ possibility theory to represent vagueness and uncertainty in class hierarchies in the object-centered model. Based on the consideration that a subclass is a specialization of a superclass, the fuzzy ranges of the subclass attributes define restrictions on the ranges of the superclass attributes.…”

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confidence: 99%

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A fuzzy object-oriented data model for managing vague and uncertain information

Bordogna

Pasi

Lucarella

1999

Int. J. Intell. Syst.

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In this paper, a fuzzy Object‐Oriented Data model (FOOD) is defined based on the extension of a Graph‐based Object model (D. Lucarella and A. Zanzi “A graph‐oriented data model,” in Database and Expert Systems Applications, R. Wagner and H. Toma, Eds., Springer‐Verlag, Berlin, 1996, pp. 197–206), in order to manage both crisp and imperfect information. These capabilities are requisites of many current applications dealing with data of different nature and with complex interrelationships. The model is based on a visual paradigm which supports both the representation of the data semantics and the direct browsing of the information. In the extended model both the database scheme and instances are represented as directed labeled graphs in which the fuzzy and uncertain information has its own representation. ©1999 John Wiley & Sons, Inc.

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Imprecision and uncertainty in the UFO database model

Cited by 21 publications

References 12 publications

Modeling fuzzy information in fuzzy extended entity-relationship model and fuzzy relational databases

Modeling fuzzy information in fuzzy extended entity-relationship model and fuzzy relational databases

Extending engineering data model for web-based fuzzy information modeling

A fuzzy object-oriented data model for managing vague and uncertain information

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