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) ...

We develop a new model for decision making under risk environment and under uncertainty. We introduce a new aggregation operator that unifies the probabilities and the ordered weighted averaging (OWA) operator in the same formulation. We call it the probabilistic ordered weighted averaging (POWA) operator. This aggregation operator provides a more complete representation of the decision problem...

A new method for decision making that uses the ordered weighted averaging (OWA) operator in the aggregation of the information is presented. It is used a concept that it is known in the literature as the index of maximum and minimum level (IMAM). This index is based on distance measures and other techniques that are useful for decision making. By using the OWA operator in the IMAM, we form a ne...

Ranking decision making units (DMUs) is one of the most important applications of data envelopment analysis (DEA). In this paper, we exploit the power of individual appreciativeness in developing a methodology that combines crossevaluation, preference voting and ordered weighted averaging (OWA). We show that each stage of the proposed methodology enhances discrimination among DMUs while offerin...

We utilize the dynamical renormalization group formalism to calculate the real space trajectory of a compact binary inspiral for long times via a systematic resummation of secularly growing terms. This method generates closed form solutions without orbit averaging, and the accuracy can be systematically improved. The expansion parameter is v5νΩðt − t0Þ where t0 is the initial time, t is the tim...

In this paper, we discuss a framework for weighted combination of classifiers for word sense disambiguation (WSD). This framework is essentially based on DempsterShafer theory of evidence (Dempster, 1967; Shafer, 1976) and ordered weighted averaging (OWA) operators (Yager, 1988). We first determine various kinds of features which could provide complementarily linguistic information for the cont...

We study a stochastic model of influence where agents have “yes” or “no” inclinations on some issue, and opinions may change due to mutual influence among the agents. Each agent independently aggregates the opinions of the other agents and possibly herself. We study influence processes modelled by ordered weighted averaging operators, which are anonymous: they only depend on how many agents sha...

Most preferred ordered weighted average (MP-OWA) operator is a new kind of neat (dynamic weight) OWA operator in the aggregation operator families. It considers the preferences of all alternatives across the criteria and provides unique aggregation characteristics in decision making. In this paper, we propose the parametric form of the MP-OWA operator to deal with the uncertainty preference inf...

In face recognition, one of the most important problems to tackle is a large amount of data and the redundancy of information contained in facial images. There are numerous approaches attempting to reduce this redundancy. One of them is information aggregation based on the results of classifiers built on selected facial areas being the most salient regions from the point of view of classificati...