Several recent works have focused on OLAP over imprecise data, where each fact can be a region, instead of a point, in a multidimensional space. They have provided a multiple-world semantics for such data, and developed efficient solutions to answer OLAP aggregation queries over the imprecise facts. These solutions however assume that the imprecise facts can be interpreted independently of one ...

ROC analysis is an important tool for evaluation and comparison of classifiers in imprecise environments (i.e., class distribution and cost parameters are unknown). Area Under the Curve of ROC (AUC) is increasingly being recognized as a better measure for evaluating algorithm performance than accuracy. A bigger AUC value implies a better ranking performance for a classifier. Linguistic decision...

The task of finding shortest paths in weighted graphs is one of the archetypical problems encountered in the domain of combinatorial optimization and has been studied intensively over the past five decades. More recently, fuzzy weighted graphs, along with generalizations of algorithms for finding optimal paths within them, have emerged as an adequate modeling tool for prohibitively complex and/...

With increase in the number of Web services, the complexity involved in finding appropriate services for the given user’s request also increases. So, selection of appropriate services has become an important task while processing the request. Initially, service selection is based on the matchmaking algorithm, but as there are number of identical and overlapping services for a single request, a ...

Web 2.0 is based on personalized access to imprecise and incomplete information from heterogeneous sources. In this paper we present a web-based system enabling preference-based search. We use modified Fagin’s model of fuzzy preferences based on aggregation of attribute preferences. Aggregation is generated by user ranking of objects. Our contributions are twofold. First we present a formal mod...

Intuitionistic fuzzy sets are suitable for capturing imprecise or uncertain decision information in multiple criteria decision analysis. In addition, optimism and pessimism generally affect the manner in which subjective judgments are construed. This paper proposes an outranking model, a QUALIFLEX method, for relating optimism and pessimism within the intuitionistic fuzzy decision environment. ...

A manufacturing inventory model with shortages with carrying cost, shortage cost, setup cost and demand quantity as imprecise numbers, instead of real numbers, namely interval number is considered here. First, a brief survey of the existing works on comparing and ranking any two interval numbers on the real line is presented. A common algorithm for the optimum production quantity (Economic lot-...

The stock selection problem is one of the major issues in the investment industry, which is mainly solved by analyzing financial ratios. However, considering the complexity and imprecise patterns of the stock market, obvious and easy-to-understand investment rules, based on fundamental analysis, are difficult to obtain. Fundamental and technical analyses are two common methods for predicting th...