This paper describes a new multi-stage technique PAKS (the abbreviation of Russian words: Consequent Aggregation of Classi ̄ed Situations) for sorting multi-attribute objects by a group. Based on decision maker preferences, this technique provides a hierarchical aggregation of a large number of initial attributes into a smaller number of criteria, thus reducing the dimension of the attribute spa...

To facilitate the analysis of real and simulated data on groups, organizations and societies tools and measures are needed that can handle relational or network data that is multi-mode, multi-link, and multi-time period, in which both nodes and edges have attributes and there are possible errors in the data. The integrated CMU dynamic network analysis toolset described in this paper enables the...

One of the most challenging goals of recommender systems is to infer the preferences of users through the observation of their actions. Those preferences are essential to obtain a satisfactory accuracy in the recommendations. Preference learning is especially difficult when attributes of different kinds (numeric or linguistic) intervene in the problem, and even more when they take multiple poss...

Glyph-based visualization is an effective tool for depicting multivariate information. Since sorting is one of the most common analytical tasks performed on individual attributes of a multi-dimensional data set, this motivates the hypothesis that introducing glyph sorting would significantly enhance the usability of glyph-based visualization. In this paper, we present a glyph-based conceptual f...

In the cloud right weight attribute encryption scheme based on multi-agency. Under existing cloud computing environment based on multi-agency access control scheme generally do not take into account the weights of the attributes that the status attributes are equal. But in real life, with the right to property values are meaningful. Each attribute in the system that served as different roles, t...

In Formal Concept Analysis, attribute reduction is a important step in order to reduce the complexity of the calculation of the concept lattice. This reduction is more complex in fuzzy environments. In this paper, we will present a first approximation to reduce the set of attributes in the multi-adjoint concept lattice.

Semantic attributes have been proposed to bridge the semantic gap between low-level feature representation and high-level semantic understanding of visual objects. Obtaining a good representation of semantic attributes usually requires learning from high-dimensional low-level features, which not only significantly increases the time and space requirement but also degrades the performance due to...

Multi-Domain learning assumes that a single metadata attribute is used in order to divide the data into so-called domains. However, real-world datasets often have multiple metadata attributes that can divide the data into domains. It is not always apparent which single attribute will lead to the best domains, and more than one attribute might impact classification. We propose extensions to two ...

Recently, the TODIM$^1$(an acronym in Portuguese of interactive and multi-criteria decision making) method has attracted increasing attention and many researchers have extended it to deal with multiple attribute decision making (MADM) problems under different situations. However, none of them can be used to handle MADM problems with positive, independent, and negative interactions among attribu...