Search Results for author: Arnaud Martin

Found 38 papers, 0 papers with code

Evidential positive opinion influence measures for viral marketing

no code implementations11 Jul 2019 Siwar Jendoubi, Arnaud Martin

We also use an influence maximization model that the set of detected influencers for each scenario.

Contributors profile modelization in crowdsourcing platforms

no code implementations19 Nov 2018 Constance Thierry, Jean-Christophe Dubois, Yolande Le Gall, Arnaud Martin

The crowdsourcing consists in the externalisation of tasks to a crowd of people remunerated to execute this ones.

Evidential community detection based on density peaks

no code implementations28 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.

Community Detection

Conflict management in information fusion with belief functions

no code implementations13 Sep 2017 Arnaud Martin

We recall in this chapter some of them and we propose a discussion to consider the conflict in information fusion with the theory of belief functions.

An automatic water detection approach based on Dempster-Shafer theory for multi spectral images

no code implementations9 Aug 2017 Na Li, Arnaud Martin, Rémi Estival

Detection of surface water in natural environment via multi-spectral imagery has been widely utilized in many fields, such land cover identification.

Preference fusion and Condorcet's Paradox under uncertainty

no code implementations9 Aug 2017 Yiru Zhang, Tassadit Bouadi, Arnaud Martin

The aim of this work is to propose a preference fusion method that copes with uncertainty and escape from the Condorcet paradox.

The Advantage of Evidential Attributes in Social Networks

no code implementations26 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.

Evidence combination for a large number of sources

no code implementations25 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.

A reliability-based approach for influence maximization using the evidence theory

no code implementations30 Jun 2017 Siwar Jendoubi, Arnaud Martin

Furthermore, the reliability-based influence measure is used with an influence maximization model to select a set of users that are able to maximize the influence in the network.

Dynamic time warping distance for message propagation classification in Twitter

no code implementations26 Jan 2017 Siwar Jendoubi, Arnaud Martin, Ludovic Liétard, Boutheina Ben Yaghlane, Hend Ben Hadji

In this paper, we are mainly interested in the classification of social messages based on their spreading on online social networks (OSN).

Dynamic Time Warping General Classification

Two Evidential Data Based Models for Influence Maximization in Twitter

no code implementations20 Jan 2017 Siwar Jendoubi, Arnaud Martin, Ludovic Liétard, Ben Hend, Ben Boutheina

In this paper, we propose two evidential influence maximization models for Twitter social network.

Social and Information Networks

Une mesure d'expertise pour le crowdsourcing

no code implementations17 Jan 2017 Hosna Ouni, Arnaud Martin, Laetitia Gros, Mouloud Kharoune, Zoltan Miklos

The evaluation of the participants work quality is a major issue in crowdsourcing.

Maximizing positive opinion influence using an evidential approach

no code implementations20 Oct 2016 Siwar Jendoubi, Arnaud Martin, Ludovic Liétard, Hend Hadji, Boutheina Yaghlane

In this paper, we propose a new data based model for influence maximization in online social networks.

Characterization of experts in crowdsourcing platforms

no code implementations30 Sep 2016 Amal Ben Rjab, Mouloud Kharoune, Zoltan Miklos, Arnaud Martin

We model such partial or incomplete responses with the help of belief functions, and we derive a measure that characterizes the expertise level of each participant.

Semi-supervised evidential label propagation algorithm for graph data

no code implementations29 Jul 2016 Kuang Zhou, Arnaud Martin, Quan Pan

In the task of community detection, there often exists some useful prior information.

Community Detection

Evidential Label Propagation Algorithm for Graphs

no code implementations13 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.

Community Detection

ECMdd: Evidential c-medoids clustering with multiple prototypes

no code implementations3 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.

The belief noisy-or model applied to network reliability analysis

no code implementations3 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.

Adaptive imputation of missing values for incomplete pattern classification

no code implementations8 Feb 2016 Zhun-Ga Liu, Quan Pan, Jean Dezert, Arnaud Martin

We propose a credal classification method for incomplete pattern with adaptive imputation of missing values based on belief function theory.

General Classification Imputation

Evidential relational clustering using medoids

no code implementations15 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.

Combining partially independent belief functions

no code implementations17 Mar 2015 Mouna Chebbah, Arnaud Martin, Boutheina Ben Yaghlane

The theory of belief functions manages uncertainty and also proposes a set of combination rules to aggregate opinions of several sources.

A Distance-Based Decision in the Credal Level

no code implementations28 Jan 2015 Amira Essaid, Arnaud Martin, Grégory Smits, Boutheina Ben Yaghlane

Second, we give experiments showing that our rule is able to decide on a set of hypotheses.

Decision Making

Inclusion within Continuous Belief Functions

no code implementations27 Jan 2015 Dorra Attiaoui, Pierre-Emmanuel Doré, Arnaud Martin, Boutheina Ben Yaghlane

Defining and modeling the relation of inclusion between continuous belief function may be considered as an important operation in order to study their behaviors.

Uncertainty in Ontology Matching: A Decision Rule-Based Approach

no code implementations23 Jan 2015 Amira Essaid, Arnaud Martin, Grégory Smits, Boutheina Ben Yaghlane

Considering the high heterogeneity of the ontologies pub-lished on the web, ontology matching is a crucial issue whose aim is to establish links between an entity of a source ontology and one or several entities from a target ontology.

Int{é}gration d'une mesure d'ind{é}pendance pour la fusion d'informations

no code implementations22 Jan 2015 Mouloud Kharoune, Arnaud Martin

Many information sources are considered into data fusion in order to improve the decision in terms of uncertainty and imprecision.

Second-Order Belief Hidden Markov Models

no code implementations22 Jan 2015 Jungyeul Park, Mouna Chebbah, Siwar Jendoubi, Arnaud Martin

The probabilistic HMMs have been one of the most used techniques based on the Bayesian model.

Classification of Message Spreading in a Heterogeneous Social Network

no code implementations22 Jan 2015 Siwar Jendoubi, Arnaud Martin, Ludovic Liétard, Boutheina Ben Yaghlane

We tested our classifier on a real word network that we collected from Twitter, and our experiments show the performance of our belief classifier.

General Classification

Trolls Identification within an Uncertain Framework

no code implementations21 Jan 2015 Imen Ouled Dlala, Dorra Attiaoui, Arnaud Martin, Boutheina Ben Yaghlane

Based on the assumption consisting on the trolls' integration in the successful discussion threads, we try to detect the presence of such malicious users.

Belief Approach for Social Networks

no code implementations20 Jan 2015 Salma Ben Dhaou, Mouloud Kharoune, Arnaud Martin, Boutheina Ben Yaghlane

In this paper, we tried to model a social network as being a network of fusion of information and determine the true nature of the received message in a well-defined node by proposing a new model: the belief social network.

Consid{é}rant la d{é}pendance dans la th{é}orie des fonctions de croyance

no code implementations20 Jan 2015 Mouna Chebbah, Mouloud Kharoune, Arnaud Martin, Boutheina Ben Yaghlane

In this paper, we propose to learn sources independence in order to choose the appropriate type of combination rules when aggregating their beliefs.

Designing a Belief Function-Based Accessibility Indicator to Improve Web Browsing for Disabled People

no code implementations20 Jan 2015 Jean-Christophe Dubois, Yolande Le Gall, Arnaud Martin

The purpose of this study is to provide an accessibility measure of web-pages, in order to draw disabled users to the pages that have been designed to be ac-cessible to them.

Belief Hierarchical Clustering

no code implementations12 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.

Evidential-EM Algorithm Applied to Progressively Censored Observations

no code implementations7 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.

Median evidential c-means algorithm and its application to community detection

no code implementations7 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.

Community Detection Graph Clustering +1

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