Modeling imprecise requirements with XML

Fanjiang, Yong-Yi

doi:10.1016/s0950-5849(03)00015-6

Cited by 34 publications

(12 citation statements)

References 9 publications

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“…XML documents with incomplete information have been researched by (Serge Abiteboul, Segoufin, & Vianu, 2006) and probabilistic data has been researched by (Nierman & Jagadish, 2002). (Lee & Fanjiang, 2003) developed a fuzzy-object-oriented modelling technique based on the XML language to model requirement specifications and incorporated the notion of stereotypes to facilitate the modelling of imprecise requirements.…”

Section: Fuzzy Xml Modellingmentioning

confidence: 99%

Securing Financial XML Transactions Using Intelligent Fuzzy Classification Techniques

Ammari

2017

Ontologies and Big Data Considerations for Effective Intelligence

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Keywords: XML, financial transactions, fuzzy logic, fuzzy XML, XML security, XML encryption, financial transactions, bankingThe eXtensible Markup Language (XML) has been widely adopted in many financial institutions in their daily transactions; this adoption was due to the flexible nature of XML providing a common syntax for systems messaging in general and in financial messaging in specific. Excessive use of XML in financial transactions messaging created an aligned interest in security protocols integrated into XML solutions in order to protect exchanged XML messages in an efficient yet powerful mechanism. However, financial institutions (i.e. banks) perform large volume of transactions on daily basis which require securing XML messages on large scale. Securing large volume of messages will result performance and resource issues. Therefore, an approach is needed to secure specified portions of an XML document, syntax and processing rules for representing secured parts.In this research we have developed a smart approach for securing financial XML transactions using effective and intelligent fuzzy classification techniques. Our approach defines the process of classifying XML content using a set of fuzzy variables.Upon fuzzy classification phase, a unique value is assigned to a defined attribute named "Importance Level". Assigned value indicates the data sensitivity for each XML tag.This thesis also defines the process of securing classified financial XML message content by performing element-wise XML encryption on selected parts defined in fuzzy

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Section: Fuzzy Xml Modellingmentioning

confidence: 99%

Securing Financial XML Transactions Using Intelligent Fuzzy Classification Techniques

Ammari

2017

Ontologies and Big Data Considerations for Effective Intelligence

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“…The fuzziness in the fuzzy XML data considered in (Lee and Fanjiang, 2003) comes from the fuzzy object-oriented modeling technique (FOOM) schema proposed in (Lee et al, 1999) because the FOOM schema is mapped to the XML schema and to the XML documents. Several kinds of fuzziness in fuzzy objects are identified in the FOOM schema, mainly including attribute with linguistic values, attribute with fuzzy sets and fuzzy classes.…”

Section: Fuzzy Data In Xml Documentsmentioning

confidence: 99%

“…The fuzzy classes directly result in fuzzy object-class relationships and fuzzy class-class relationships. Lee and Fanjiang (2003) introduce some new elements in the fuzzy XML documents, mainly including: "discrete-fuzzy-set", "object" and "membership-degree" for the discrete fuzzy sets; "fuzzy-set", "point", "f-value" and "membership-degree" for the continuous fuzzy sets; "fuzzy-attribute", "name", "fuzzy-range" and "linguistic-value" for the fuzzy attributes with linguistic values (on the continuous universe of discourse); "fuzzy-attribute", "name", "fuzzy-range", "typical-value" and "t-degree" for the fuzzy attributes with typical values (on the discrete universe of discourse). Also they introduce several new elements in the fuzzy XML documents for the representations of fuzzy rules and fuzzy associations.…”

Section: Fuzzy Data In Xml Documentsmentioning

confidence: 99%

Modeling fuzzy data with XML: A survey

2016

Fuzzy Sets and Systems

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“…Consequently, it is important to specify not only how system objects interact to achieve the goal of each base use case, but also how these objects interact to implement the crosscutting concerns of each aspectual use case as well as where the effects take places with respect to the aspectual use case's corresponding base use cases. As a continuation of our previous research, [8][9][10]24 we augment the use case speciÞcation with aspectual property to document the responsibility of an aspectual use case. Through the speciÞcation of aspectual property, aspectual behavior can be modeled within the proposed aspectual sequence diagrams together with three types of aspectual interaction operators to perform on the base use cases.…”

Section: Aspectual Behaviors Modelingmentioning

confidence: 99%

Aspect-enhanced goal-driven sequence diagram

Lee

Hsu

2010

Int. J. Intell. Syst.

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Recently, aspect-oriented approaches have resulted in a tremendous impact on the processing of broadly scoped properties during the development of software systems. However, the weaving mechanism of these crosscutting concerns cannot be easily represented with the extant uniÞed modeling language (UML) notation at the early stage of software development life cycle. As an attempt toward the investigation of how the crosscutting behavior takes place, we proposed, in this work, an aspect-enhanced goal-driven approach to modeling the aspectual behavior in UML state transition diagrams and sequence diagrams with the proposed interaction operators based on the aspectual weaving semantics. By introducing the proposed interaction operations in the UML combined fragment, UML sequence diagrams can be further enhanced to support the modeling of the interactions between aspectual and base behavior in the analysis and design stage of software development. To further exemplify our points, the meeting scheduler system is chosen as a vehicle to illustrate the proposed approach. C

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Modeling imprecise requirements with XML

Cited by 34 publications

References 9 publications

Securing Financial XML Transactions Using Intelligent Fuzzy Classification Techniques

Securing Financial XML Transactions Using Intelligent Fuzzy Classification Techniques

Modeling fuzzy data with XML: A survey

Aspect-enhanced goal-driven sequence diagram

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