6,014 research outputs found
Semantic distillation: a method for clustering objects by their contextual specificity
Techniques for data-mining, latent semantic analysis, contextual search of
databases, etc. have long ago been developed by computer scientists working on
information retrieval (IR). Experimental scientists, from all disciplines,
having to analyse large collections of raw experimental data (astronomical,
physical, biological, etc.) have developed powerful methods for their
statistical analysis and for clustering, categorising, and classifying objects.
Finally, physicists have developed a theory of quantum measurement, unifying
the logical, algebraic, and probabilistic aspects of queries into a single
formalism. The purpose of this paper is twofold: first to show that when
formulated at an abstract level, problems from IR, from statistical data
analysis, and from physical measurement theories are very similar and hence can
profitably be cross-fertilised, and, secondly, to propose a novel method of
fuzzy hierarchical clustering, termed \textit{semantic distillation} --
strongly inspired from the theory of quantum measurement --, we developed to
analyse raw data coming from various types of experiments on DNA arrays. We
illustrate the method by analysing DNA arrays experiments and clustering the
genes of the array according to their specificity.Comment: Accepted for publication in Studies in Computational Intelligence,
Springer-Verla
Zadeh's Centenary
This is the introductory paper in a special issue on fuzzy logic dedicated to the centenary of the birth of Lotfi A. Zadeh published by International Journal of Computers Communications & Control (IJCCC). In 1965, Lotfi A. Zadeh published in the journal „Information and Control” the article titled „Fuzzy sets”, which today reaches over 117 thousand citations. The total sum of citations for all his papers is above 253 thousand. Based on the notion of fuzzy sets, fuzzy logic and the concept of soft computing emerged, bringing extremely important implications to the field of Artificial Intelligence (AI). In 2017, I published, whith F.G. Filip and M.J. Manolescu, a 42-page long paper in the IJCCC about the life and masterwork of Lotfi A. Zadeh, from which I will use some information in this material [15]
The First Steps in Fuzzy Set Theory in France Forty Years Ago
International audienceAt the occasion of the fiftieth anniversary of the founding article “Fuzzy sets” by L. A. Zadeh, we briefly outline the beginnings of fuzzy set research in France some ten years later, pointing out the pioneering role of Arnold Kaufmann and few other
Soft data mining, computational theory of perceptions, and rough-fuzzy approach
Data mining and knowledge discovery is described from pattern recognition point of view along with the relevance of soft computing. Key features of the computational theory of perceptions and its significance in pattern recognition and knowledge discovery problems are explained. Role of fuzzy-granulation (f-granulation) in machine and human intelligence, and its modeling through rough-fuzzy integration are discussed. Merits of fuzzy granular computation, in terms of performance and computation time, for the task of case generation in large scale case-based reasoning systems are illustrated through an example
Soft Computing for Robust Secure Wireless Reception
Soft computing is a collection of different computing methodologies that include neuro computing, fuzzy logic, evolutionary computing, and probabilistic reasoning. These are aimed to exploit the tolerance for imprecision and uncertainty to achieve tractability, robustness, and low solution cost. This paper presents a brief overview of soft computing components, followed by typical realization, via simulation of a wireless receiver employing a hybrid soft computing technique to illustrate its application in a fading signal propagation scenario.Defence Science Journal, 2009, 59(5), pp.517-523, DOI:http://dx.doi.org/10.14429/dsj.59.155
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