9 research outputs found

    Classification of Message Spreading in a Heterogeneous Social Network

    Get PDF
    Nowadays, social networks such as Twitter, Facebook and LinkedIn become increasingly popular. In fact, they introduced new habits, new ways of communication and they collect every day several information that have different sources. Most existing research works fo-cus on the analysis of homogeneous social networks, i.e. we have a single type of node and link in the network. However, in the real world, social networks offer several types of nodes and links. Hence, with a view to preserve as much information as possible, it is important to consider so-cial networks as heterogeneous and uncertain. The goal of our paper is to classify the social message based on its spreading in the network and the theory of belief functions. The proposed classifier interprets the spread of messages on the network, crossed paths and types of links. We tested our classifier on a real word network that we collected from Twitter, and our experiments show the performance of our belief classifier

    Second-Order Belief Hidden Markov Models

    Get PDF
    Hidden Markov Models (HMMs) are learning methods for pattern recognition. The probabilistic HMMs have been one of the most used techniques based on the Bayesian model. First-order probabilistic HMMs were adapted to the theory of belief functions such that Bayesian probabilities were replaced with mass functions. In this paper, we present a second-order Hidden Markov Model using belief functions. Previous works in belief HMMs have been focused on the first-order HMMs. We extend them to the second-order model

    Modelling and Fusion of Imperfect Implication Rules

    No full text
    In this paper, we develop a method to find the uncertain consequent by fusing the uncertain antecedent and the uncertain implication rule. In particular with Dempster-Shafer theoretic models utilized to capture the uncertainty intervals associated with the antecedent and the rule itself, we derive bounds on the confidence interval associated with the rule consequent. We derive inequalities for the belief and plausibility values of the consequent and with least commitment choice they become equations. We also demonstrate the consistency of our model with probability and classical logic

    Sistematización diagnostica y caracterización de las enfermedades de tres especies ícticas explotadas en Colombia y fisiopatología de la enfermedad septicémica

    No full text
    IP 1101-09-321-97Falta anexo No 4.v.1 Informe final. -- v.2 Guias de diagnostico anatomopatologicode pecesen Colombia. -- v.3 Fisiopatologia e inmunohistoquimica de la infeccion experimental inducidaporaeromonas hydrophilia en tilapia roja (Oreochromis spp) / Carlos Aregui C. -- v.4 Patologia de los peces en Colombia / Carlos A. Aregui Castro, Noel Verjan Garcia. -- v.5 Caracterizacion de las enfermedadesde latilapia roja (oreochromis sp.) cultivada en el departamento del Tolima, sistematizacion de la informaciony fisiopatologia de la enfermedad septicemica.[et.al] -- En: Jornada de acuicultura Sanidad de peces (3: 1999jul. 29 :Villavicencio, Colombia) --;PONENCIA(S) EN CONGRESO: Reporte de streptococosis en tilapiascultivadasen Colombia / Andres Pulido B. ...;Vol. 24, no. 3 (sep. 1999); p.18-25. -- ISSN 01201530;Prevalencia de las principales lesiones encontradas en tilapiaroja (Oreochromis sp.) cultivadas en el;departamento del Tolima / Alba Lucia Rey C., Carlos IreguiC.--En: Jornada de acuicultura sanidad de peces;(4 : 2000 ago. 18 : Villavicencio, Colombia) -- Reporte destreptococosisen tilapias cultivadas en Colombia /;Andres Pulido, Carlos Iregui, Judith Figueroa. -- En: Acuicultura en Armonia con el Ambiente (1999 nov. 17-20;: Puerto la Cruz, Venezuela) -- Metodologia para la toma yenviode muestras para diagostico de enfermedades;de los peces / Carlos Iregui, Pedro Rene Eslava. -- En: Jornadade Acuicultura Sanidad en Peces (3 : 1999 jul.;29 : Villavicencio, Colombia) -- ARTICULO(S) EN REVISTA: Descripcion de uncaso de mixosporidiasis clinica en;cachama blanca, Piaractus brachypomus / Carlos Iregui ...[et.al]. -- En:Dahlia: Revista de la Asociacion;Colombiana de Ictiologos. -- No. 3 (1999); p. 17-29. -- ISSN 01229982. --Proteinas sericas de la cachama;blanca (Piarcactus brachypomus) en condiciones de cultivo/ N.Verjan ...[et.al]. -- En: Revista Acovez. -

    Dynamic Time Warping Distance for Message Propagation Classification in Twitter

    Get PDF
    International audienceSocial messages classification is a research domain that has attracted the attention of many researchers in these last years. Indeed, the social message is different from ordinary text because it has some special characteristics like its shortness. Then the development of new approaches for the processing of the social message is now essential to make its classification more efficient. In this paper, we are mainly interested in the classification of social messages based on their spreading on online social networks (OSN). We proposed a new distance metric based on the Dynamic Time Warping distance and we use it with the probabilistic and the evidential k Nearest Neighbors (k-NN) classifiers to classify propagation networks (PrNets) of messages. The propagation network is a directed acyclic graph (DAG) that is used to record propagation traces of the message, the traversed links and their types. We tested the proposed metric with the chosen k-NN classifiers on real world propagation traces that were collected from Twitter social network and we got good classification accuracies

    Correction of Belief Function to Improve the Performances of a Fusion System

    No full text
    International audienceOur application concerns the fusion of classifiers for the recognition of trees from their leaves, in the framework of belief functions theory. In order to improve the rate of good classification it is necessary to correct Bayesian mass functions. This correction will be done from the meta-knowledge which is estimated from the confusion matrix. The corrected mass functions considerably improve the recognition rate based on the decisions provided by the classifiers
    corecore