66 research outputs found
Some notes on an extended query language for FSM
FSM is a database model that has been recently proposed by the authors. FSM uses basic concepts of
classification, generalization, aggregation and association that are commonly used in semantic modelling and
supports the fuzziness of real-world at attribute, entity, class and relations intra and inter-classes levels. Hence, it
provides tools to formalize and conceptualize real-world within a manner adapted to human perception of and
reasoning about this real-word. In this paper we briefly review basic concepts of FSM and provide some notes on an
extended query language adapted to it.ou
Conceptual design and implementation of the fuzzy semantic model
FSM is one of few database models that support
fuzziness, uncertainty and impreciseness of real-world at the class
deïŹnition level. FSM authorizes an entity to be partially member
of its class according to a given degree of membership that reïŹects
the level to which the entity veriïŹes the extent properties of this
class. This paper deals with the conceptual design of FSM and
adresses some implementation issues.ou
Incorporating stakeholdersâ knowledge in group decision-making
International audienc
Aggregation procedure based on majority principle for collective identification of firmâs crucial knowledge
It is very important to identify, preserve, and transfer knowledge to those who need it within firm. However, the identification of knowledge and especially tacit knowledge is a complex process because knowledge cannot be measured quantitatively. In this paper we present an approach for inducing a set of collective decision rules representing a generalized description of the preferential information of a group of decision makers involved in a multicriteria classification problem to identify crucial knowledge to be capitalized
Extending fuzzy semantic model by advanced decision rules
This paper extends FSM, a recently proposed semantic data model that supports fuzziness, imprecision and uncertainty of real-world. More precisely, the paper proposes four new concepts, decisional grouping, inhibition, multiplicity and selection, which allows enhancing the modeling of real-world applications. It integrates these concepts in FSM by the definition of new decision rules
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