no code implementations • 7 Jan 2015 • Kuang Zhou, Arnaud Martin, Quan Pan
Evidential-EM (E2M) algorithm is an effective approach for computing maximum likelihood estimations under finite mixture models, especially when there is uncertain information about data.
no code implementations • 7 Jan 2015 • Kuang Zhou, Arnaud Martin, Quan Pan, Zhun-Ga Liu
In this paper, a new prototype-based clustering method, called Median Evidential C-Means (MECM), which is an extension of median c-means and median fuzzy c-means on the theoretical framework of belief functions is proposed.
no code implementations • 12 Jan 2015 • Wiem Maalel, Kuang Zhou, Arnaud Martin, Zied Elouedi
In the data mining field many clustering methods have been proposed, yet standard versions do not take into account uncertain databases.
no code implementations • 15 Jul 2015 • Kuang Zhou, Arnaud Martin, Quan Pan, Zhun-Ga Liu
Medoid-based clustering algorithms, which assume the prototypes of classes are objects, are of great value for partitioning relational data sets.
no code implementations • 3 Jun 2016 • Kuang Zhou, Arnaud Martin, Quan Pan
In this paper, an extension of NOR model based on the theory of belief functions, named Belief Noisy-OR (BNOR), is proposed.
no code implementations • 3 Jun 2016 • Kuang Zhou, Arnaud Martin, Quan Pan, Zhun-Ga Liu
In the application of FCMdd and original ECMdd, a single medoid (prototype), which is supposed to belong to the object set, is utilized to represent one class.
no code implementations • 13 Jun 2016 • Kuang Zhou, Arnaud Martin, Quan Pan, Zhun-Ga Liu
With the increasing size of social networks in real world, community detection approaches should be fast and accurate.
no code implementations • 29 Jul 2016 • Kuang Zhou, Arnaud Martin, Quan Pan
In the task of community detection, there often exists some useful prior information.
no code implementations • 25 Jul 2017 • Kuang Zhou, Arnaud Martin, Quan Pan
It will keep the spirit of the conjunctive rule to reinforce the belief on the focal elements with which the sources are in agreement.
no code implementations • 26 Jul 2017 • Salma Ben Dhaou, Kuang Zhou, Mouloud Kharoune, Arnaud Martin, Boutheina Ben Yaghlane
In this paper, we will present how we detect communities in graphs with uncertain attributes in the first step.
no code implementations • 28 Sep 2018 • Kuang Zhou, Quan Pan, Arnaud Martin
Credal partitions in the framework of belief functions can give us a better understanding of the analyzed data set.