This paper addresses the blog distillation problem, that is, given a user query find the blogs that are most related to the query topic. We model each post as evidence of the relevance of a blog to the query, and use aggregation methods like Ordered Weighted Averaging (OWA) operators to combine the evidence. We show that using only highly relevant evidence (posts) for each blog can result in an...

Aggregation functions are mathematical operators that merge given data in order to obtain a global value that preserves the information given by the data as much as possible. In most practical applications, this value is expected to be between the infimum and the supremum of the given data, which is guaranteed only when the aggregation functions are idempotent. Ordered weighted averaging (OWA) ...

The weighted ordered weighted averaging(WOWA) operator introduced by Torra is an important aggregation technique, which includes the famous weighted averaging(WA) operator and the ordered weighted averaging(OWA) operator as special cases. In this paper, we introduce a new hesitant fuzzy decision making technique called the hesitant fuzzy weighted OWA(HFWOWA) operator. It is an extension of the ...

This paper presents a fuzzy extension of TOPSIS (technique for order performance by similarity to ideal solution) with a new quantifier guided distance metric and majority opinion aggregator for multi-criteria decision making in a group decision environment. The proposed distance metric is based on OWA aggregators and provides an opportunity to use linguistic quantifiers to have linguistic defi...

for some α (0≤α< 1). We say that f(z) is in the class ∑C(α) of such functions. The class ∑∗(α) and various other subclasses of ∑ have been studied rather extensively by Nehari and Netanyahu [9], Clunie [4], Pommerenke [11, 12], Miller [7], Royster [13], and others (cf., e.g., Bajpai [2], Goel and Sohi [6], Mogra et al. [8], Uralegaddi and Ganigi [15], Cho et al. [3], Aouf [1], and Uralegaddi an...

In this contribution we propose a method for generating OWA weighting vectors from the individual assessments on a set of alternatives in such a way that these weights minimize the disagreement among individual assessments and the outcome provided by the OWA operator. For measuring that disagreement we have aggregated distances between individual and collective assessments by using a metric and...

The concepts of system load and capacity are pivotal in risk analysis. The complexity in risk analysis increases when the input parameters are either stochastic (aleatory uncertainty) and/or missing (epistemic uncertainty). The aleatory and epistemic uncertainties related to input parameters are handled through simulation-based parametric and non-parametric probabilistic techniques. The complex...

Ordered weighted averaging (OWA) operators and their extensions are powerful tools used in numerous decision-making problems. This class of operator belongs to a more general family of aggregation operators, understood as discrete Choquet integrals. Aggregation operators are usually characterized by indicators. In this article four indicators usually associated with the OWA operator are extende...

In several economic fields, such as those related to health, education or poverty, the individuals’ characteristics are measured by bounded variables. Accordingly, these characteristics may be indistinctly represented by achievements or shortfalls. A difficulty arises when inequality needs to be assessed. One may focus either on achievements or on shortfalls but the respective inequality rankin...

A hybrid approach integrating OWA (Ordered Weighted Averaging) aggregation into TOPSIS (technique for order performance by similarity to ideal solution) is proposed to tackle multiple criteria decision analysis (MCDA) problems. First, the setting of extreme points (ideal and anti-ideal points) in TOPSIS is redefined and extended for handling the multiple extreme points situation where a decisio...