This paper proposes a grey interval relation TOPSIS for the decision making in which all of the attribute weights and attribute values are given by the interval grey numbers. The feature of our method different from other grey relation decision-making is that all of the subjective and objective weights are obtained by interval grey number and that decisionmaking is performed based on the relati...

The basis of many systems that integrate data from multiple sources is a set of correspondences between source schemata and a target schema. Correspondences express a relationship between sets of source attributes, possibly from multiple sources, and a set of target attributes. Clio is an integration tool that assists users in de ning value correspondences between attributes [1]. In real life s...

The purpose of this paper is to extend a new balancing and ranking method to handle uncertainty for a multiple attribute analysis under a hesitant fuzzy environment. The presented hesitant fuzzy balancing and ranking (HF-BR) method does not require attributes’ weights through the process of multiple attribute decision making (MADM) under hesitant conditions. For the rating of possible alternati...

the recent years have witnessed an increasing attention to the methods of multiple attribute decision making in solving the problems of the real world due to their shorter time of calculation and easy application. one of these methods is the ‘permutation method’ which has a strong logic in connection with ranking issues, but when the number of alternatives increases, solving problems through th...

Matching query interfaces is a critical step in data integration across multiple Web databases. The problem is closely related to schema matching that typically exploits different features of schemas. Relying on a particular feature of schemas is not sufficient. We propose an evidential approach to combining multiple matchers using Dempster-Shafer theory of evidence. First, our approach views t...

Constructing fact tables and performing OLAP operations are some of the most essential but expensive operations in data warehousing. OLAP operations require aggregation on many combinations of each dimension attribute. As the number of dimensions increase, it becomes very expensive to compute summary data cubes because the cost of required computations grows exponentially with the increase of n...

A number of approaches have been proposed to determine the weights for multiple attribute decision making. However, resultant are usually assumed be fixed, making it lack tolerance accommodate variation if patterns subsequent data subject change. This article proposes a method facilitate adjustment weights, which accommodates relevant characteristics. model is first constructed that able expres...