in this work, we define a fuzzy soft set theory and its related properties. we then define fuzzy soft aggregation operator that allows constructing more efficient decision making method. finally, we give an example which shows that the method can be successfully applied to many problems that contain uncertainties.

the article suggests an algorithm for regular classifier ensemble methodology. the proposed methodology is based on possibilistic aggregation to classify samples. the argued method optimizes an objective function that combines environment recognition, multi-criteria aggregation term and a learning term. the optimization aims at learning backgrounds as solid clusters in subspaces of the high-dim...

Many software projects today are based on the integration of independently designed software components that are acquired on the market, rather than developed within the project itself. A component standard, or integration architecture, is a set of design rules meant to ensure that such components can be integrated in defined ways without undue effort. The rules of a component standard define, ...

Article history: Received 26 April 2010 Accepted 18 January 2011 Available online 21 February 2011 IT-based Service Economy requires Service Markets to flourish for the trade of services. A market does not represent a simple buyer-seller relationship, rather it is the culmination point of a complex chain of stake-holders with a hierarchical integration of value along each point in the chain. To...

In this paper, we propose a framework for a class of learning problems that we refer to as “learning to aggregate”. Roughly, learningto-aggregate problems are supervised machine learning problems, in which instances are represented in the form of a composition of a (variable) number on constituents; such compositions are associated with an evaluation, score, or label, which is the target of the...

The ranking aggregation problem is that to establishing a new aggregate ranking given a set of rankings of a finite set of items. This problem is met in various applications, such as the combination of user preferences, the combination of lists of documents retrieved by search engines and the combination of ranked gene lists. In the literature, the ranking aggregation problem has been solved as...

For more than a decade, OLAP and multidimensional analysis have generated methodologies, tools and resource management systems for the analysis of numeric data. With the growing availability of semistructured data there is a need for incorporating text-rich document data in a data warehouse and providing adapted multidimensional analysis. This paper presents a new aggregation function for keywo...

A full equilibrium treatment of molecular aggregation is presented for prototypes of 1D and 3D aggregates, with and without nucleation. By skipping complex kinetic parameters like aggregate size-dependent diffusion, the equilibrium treatment allows us to predict directly time-independent quantities such as critical concentrations. The relationships between the macroscopic equilibrium constants ...

Aggregation refers to the process of combining numerical values x1, . . . , xm into a single one M (x1, . . . , xm), so that the final result of aggregation takes into account all the individual values. In decision making, values to be aggregated are typically preference or satisfaction degrees and thus belong to the unit interval [0, 1]. This paper aims at investigating the Sugeno integral whi...

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