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A new curve fitting based rating prediction algorithm for recommender systems

Yilmaz Ar, Şahin Emrah Amrahov, Nizami A. Gasilov, Sevgi Yigit-Sert (2022)

Kybernetika

The most algorithms for Recommender Systems (RSs) are based on a Collaborative Filtering (CF) approach, in particular on the Probabilistic Matrix Factorization (PMF) method. It is known that the PMF method is quite successful for the rating prediction. In this study, we consider the problem of rating prediction in RSs. We propose a new algorithm which is also in the CF framework; however, it is completely different from the PMF-based algorithms. There are studies in the literature that can increase...

Agent-oriented abstraction.

Jacques Calmet, Pierre Maret, Regine Endsuleit (2004)

RACSAM

We define an agent-oriented abstraction formalism devoted to generalized theories of abstraction that have been proposed in Artificial Intelligence. The model we propose extends the abstraction capabilities of the existing Agent-Oriented Programming paradigm. This short note reviews first the existing attempts to define abstraction in AI and in agent systems. Then, our model is introduced in terms of six definitions covering the concepts of agents, annotated knowledge, utility and society of agents....

Comparative analysis of noise robustness of type 2 fuzzy logic controllers

Emanuel Ontiveros-Robles, Patricia Melin, Oscar Castillo (2018)

Kybernetika

Nowadays Fuzzy logic in control applications is a well-recognized alternative, and this is thanks to its inherent advantages as its robustness. However, the Type-2 Fuzzy Logic approach, allows managing uncertainty in the model. Type-2 Fuzzy Logic has recently shown to provide significant improvement in image processing applications, however it is also important to analyze its impact in controller performance. This paper is presenting a comparison in the robustness of Interval Type-2 and Generalized...

Towards a logic of semiotic systems

Constantin Thiopoulos (1992)

Mathématiques et Sciences Humaines

The rationalistic denotational approach to semantics is not adequate for capturing the structural dimension of meaning, which is immanent in semiotic systems. The demand for a structural approach to semantics is intensified by a turn in Artificial Intelligence, introduced by Connectionism and Information Retrieval. This paper presents such a structural approach to semantics founded on the phenomenological and autopoietic paradigms and proposes a formalization with the help of category theory.

What machines can and cannot do.

Luis M. Laita, Roanes-Lozano, Luis De Ledesma Otamendi (2007)

RACSAM

In this paper, the questions of what machines cannot do and what they can do will be treated by examining the ideas and results of eminent mathematicians. Regarding the question of what machines cannot do, we will rely on the results obtained by the mathematicians Alan Turing and Kurt G¨odel. Turing machines, their purpose of defining an exact definition of computation and the relevance of Church-Turing thesis in the theory of computability will be treated in detail. The undecidability of the “Entscheidungsproblem”...

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