Multiple Criteria Decision Making or multi-attribute (MCDM) problems refer to performing preference decisions (e.g. ranking, ordering, prioritization, selection) over several available alternatives or objects that are characterized by multiple, usually conflicting, attributes or criteria. MCDM techniques have been and are still being encountered in a wide range of human activities, from the pro...

Decision makers are commonly challenged with comparing, and ultimately ranking, elements regards to the degree which they satisfy multiple criteria in terms of their own preferences. This calls for a new decision making framework, we formally present here. Within such multi-criteria lex-cel: method ranking single elements. Furthermore, establish that our contributions generalise recent results ...

multi attribute decision making methods are considered as one of the most useful methods for solving ranking problems. in some decision making problems, while the alternatives for corresponding criteria are compared in a pairwise comparison manner, if the criteria are inherently fuzzy, debates will arise in ranking alternatives due to the closeness of the values of the criteria. in this researc...

Many applications in information retrieval, natural language processing, data mining, and related fields require a ranking of instances with respect to a specified criteria as opposed to a classification. Furthermore, for many such problems, multiple established ranking models have been well studied and it is desirable to combine their results into a joint ranking, a formalism denoted as rank a...

Items from a database are often ranked based on a combination of multiple criteria. A user may have the flexibility to accept combinations that weigh these criteria differently, within limits. On the other hand, this choice of weights can greatly affect the fairness of the produced ranking. In this paper, we develop a system that helps users choose criterion weights that lead to greater fairnes...

As regards of the necessity of ranking efficient units different Data Envelopment Analysis (DEA) models are introduced. Each of the existing models has advantages and deals with ranking efficient units from special aspects. But, there exist no model has all these benefits in a unified manner. The aim of this paper is to present a new ranking method which can incorporate, to a great extent, adva...

Big data sizes are constantly increasing. Big data analytics is where advanced analytic techniques are applied on big data sets. Analytics based on large data samples reveals and leverages business change. The popularity of big data analytics platforms, which are often available as open-source, has not remained unnoticed by big companies. Google uses MapReduce for PageRank and inverted indexes....