Informacja

Drogi użytkowniku, aplikacja do prawidłowego działania wymaga obsługi JavaScript. Proszę włącz obsługę JavaScript w Twojej przeglądarce.

Wyszukujesz frazę "collaborative clustering" wg kryterium: Temat


Wyświetlanie 1-4 z 4
Tytuł:
Impact of learners’ quality and diversity in collaborative clustering
Autorzy:
Rastin, Parisa
Matei, Basarab
Cabanes, Guénaël
Grozavu, Nistor
Bennani, Younés
Powiązania:
https://bibliotekanauki.pl/articles/91600.pdf
Data publikacji:
2019
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
collaborative clustering
topological neural networks
unsupervised learning
diversity
quality
Opis:
Collaborative Clustering is a data mining task the aim of which is to use several clustering algorithms to analyze different aspects of the same data. The aim of collaborative clustering is to reveal the common underlying structure of data spread across multiple data sites by applying clustering techniques. The idea of collaborative clustering is that each collaborator shares some information about the segmentation (structure) of its local data and improve its own clustering with the information provided by the other learners. This paper analyses the impact of the quality and the diversity of the potential learners to the quality of the collaboration for topological collaborative clustering algorithms based on the learning of a Self-Organizing Map (SOM). Experimental analysis on real data-sets showed that the diversity between learners impact the quality of the collaboration. We also showed that some internal indexes of quality are a good estimator of the increase of quality due to the collaboration.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2019, 9, 2; 149-165
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
A new mechanism for data visualization with TSK-type preprocessed collaborative fuzzy rule based system
Autorzy:
Prasad, M.
Liu, Y.-T.
Li, D.-L.
Lin, C. -T.
Shah, R. R.
Kaiwartya, O. P.
Powiązania:
https://bibliotekanauki.pl/articles/91743.pdf
Data publikacji:
2017
Wydawca:
Społeczna Akademia Nauk w Łodzi. Polskie Towarzystwo Sieci Neuronowych
Tematy:
fuzzy interference system
collaborative clustering
fuzzy logic
big data
data visualization
Opis:
A novel data knowledge representation with the combination of structure learning ability of preprocessed collaborative fuzzy clustering and fuzzy expert knowledge of TakagiSugeno-Kang type model is presented in this paper. The proposed method divides a huge dataset into two or more subsets of dataset. The subsets of dataset interact with each other through a collaborative mechanism in order to find some similar properties within eachother. The proposed method is useful in dealing with big data issues since it divides a huge dataset into subsets of dataset and finds common features among the subsets. The salient feature of the proposed method is that it uses a small subset of dataset and some common features instead of using the entire dataset and all the features. Before interactions among subsets of the dataset, the proposed method applies a mapping technique for granules of data and centroid of clusters. The proposed method uses information of only half or less/more than the half of the data patterns for the training process, and it provides an accurate and robust model, whereas the other existing methods use the entire information of the data patterns. Simulation results show the proposed method performs better than existing methods on some benchmark problems.
Źródło:
Journal of Artificial Intelligence and Soft Computing Research; 2017, 7, 1; 33-46
2083-2567
2449-6499
Pojawia się w:
Journal of Artificial Intelligence and Soft Computing Research
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Application of agglomerative and partitional algorithms for the study of the phenomenon of the collaborative economy within the tourism industry
Autorzy:
Pérez-Rocha, Juan Manuel
Soria-Alcaraz, Jorge Alberto
Guerrero-Rodriguez, Rafael
Purata-Sifuentes, Omar Jair
Espinal, Andrés
Sotelo-Figueroa, Marco Aurelio
Powiązania:
https://bibliotekanauki.pl/articles/385106.pdf
Data publikacji:
2020
Wydawca:
Sieć Badawcza Łukasiewicz - Przemysłowy Instytut Automatyki i Pomiarów
Tematy:
clustering tools
tourism industry
collaborative economy
Opis:
This research discusses the application of two different clustering algorithms (agglomerative and partitional) to a set of data derived from the phenomenon of the collaborative economy in the tourism industry known as Airbnb. In order to analyze this phenomenon, the algorithms are known as “hierarchical Tree” and “K-Means” were used with the objective of gaining a better understanding of the spatial configuration and current functioning of this complimentary lodging offer. The city of Guanajuato, Mexico was selected as the case for convenience purposes and the main touristic attractions were used as parameters to conduct the analysis. Cluster techniques were applied to both algorithms and the results were statistically compared.
Źródło:
Journal of Automation Mobile Robotics and Intelligent Systems; 2020, 14, 1; 81-86
1897-8649
2080-2145
Pojawia się w:
Journal of Automation Mobile Robotics and Intelligent Systems
Dostawca treści:
Biblioteka Nauki
Artykuł
Tytuł:
Relations of granular worlds
Autorzy:
Pedrycz, W.
Vukovich, G.
Powiązania:
https://bibliotekanauki.pl/articles/908015.pdf
Data publikacji:
2002
Wydawca:
Uniwersytet Zielonogórski. Oficyna Wydawnicza
Tematy:
elektrotechnika
granular computing
clustering
models of collaborative computing
fuzzy models
collaboration and competition
FCM
granular modeling
Opis:
In this study, we are concerned with a two-objective development of information granules completed on a basis of numeric data. The first goal of this design concerns revealing and representing a structure in a data set. As such it is very much oriented towards coping with the underlying relational aspects of the experimental data. The second goal deals with a formation of a mapping between information granules constructed in two spaces (thus it concentrates on the directional aspect of information granulation). The quality of the mapping is directly affected by the information granules over which it operates, so in essence we are interested in the granules that not only reflect the data but also contribute to the performance of such a mapping. The optimization of information granules is realized through a collaboration occurring at the level of the data and the mapping between the data sets. The operational facet of the problem is cast in the realm of fuzzy clustering. As the standard techniques of fuzzy clustering (including a well-known approach of FCM) are aimed exclusively at the first objective identified above, we augment them in order to accomplish sound mapping properties between the granules. This leads to a generalized version of the FCM (and any other clustering technique for this matter). We propose a generalized version of the objective function that includes an additional collaboration component to make the formed information granules in rapport with the mapping requirements (that comes with a directional component captured by the information granules). The additive form of the objective function with a modifiable component of collaborative activities makes it possible to express a suitable level of collaboration and to avoid a phenomenon of potential competition in the case of incompatible structures and the associated mapping. The logic-based type of the mapping (that invokes the use of fuzzy relational equations) comes ...
Źródło:
International Journal of Applied Mathematics and Computer Science; 2002, 12, 3; 347-357
1641-876X
2083-8492
Pojawia się w:
International Journal of Applied Mathematics and Computer Science
Dostawca treści:
Biblioteka Nauki
Artykuł
    Wyświetlanie 1-4 z 4

    Ta witryna wykorzystuje pliki cookies do przechowywania informacji na Twoim komputerze. Pliki cookies stosujemy w celu świadczenia usług na najwyższym poziomie, w tym w sposób dostosowany do indywidualnych potrzeb. Korzystanie z witryny bez zmiany ustawień dotyczących cookies oznacza, że będą one zamieszczane w Twoim komputerze. W każdym momencie możesz dokonać zmiany ustawień dotyczących cookies