Éditeur(s) : Kluwer
Résumé : We reviewed the literature concerning fish aggregation devices (FADs) to determine areas of relative research deficiency. Using specific searches of the Aquatic Sciences and Fisheries Abstracts ( ASFA) database from 1978 to December 2003 and a classical search of the pre-1978 literature, we collected 407 references on FADs. Publications before 1980 were predominantly peer-reviewed, although non-peer reviewed literature has dominated since 1980, due to the numerous technical reports produced as FADs became more widely used in artisinal and large-scale industrial. sheries in the 1980s. Most studies of the ecology of FAD-associated fish were descriptive, with few mensurative experimental studies and even fewer manipulative experimental studies that tested specific hypotheses, due to inherent difficulties in working in the open ocean on objects that are temporary in space and time. Research on the ecology of FAD-associated fish has focused on moored FADs, despite the major FAD-based. sheries being around drifting FADs. Publications presenting information on moored FADs outnumbered papers on drifting FADs by a ratio of 3.5: 1. We recommend that greater emphasis be placed by. sheries scientists and funding agencies on researching drifting FADs to provide better information for management of large-scale FAD-based industrial. sheries. Future research should focus on determining the patterns of use of drifting FADs by pelagic species, the underlying sensory processes of attraction and the ecological consequences for individual fish stocks and the wider pelagic ecosystem of the use of FADs as. sheries enhancement tools.
Reviews in Fish Biology and Fisheries (0960-3166) (Kluwer), 2004-03 , Vol. 14 , N. 1 , P. 21-42

Droits : 2004 Springer
http://archimer.ifremer.fr/doc/2004/publication-721.pdf
DOI:10.1007/s11160-004-3151-x
http://archimer.ifremer.fr/doc/00000/721/

Éditeur(s) : HAL CCSD IGI Global
Résumé : International audience
Standard data mining techniques have been applied and adapted for eliciting knowledge from social networks, by achieving classical tasks such as classification, search for frequent patterns or link prediction. Most works have exploited only the network topological structure, and therefore cannot be used to answer questions involving nodes features. For instance, the frequent pattern discovery task generally refers to the search for sub-networks frequently found in a single network or in a set of networks. In the same area, this paper focuses on the concept of frequent link that stands as a regularity found in a network on links between node groups that share common characteristics. The extraction of such links from a social network is a particularly challenging and computationally intensive problem, since it is much dependent on the number of links and attributes. In this study, we propose a solution for reducing the search space of frequent links, by filtering the nodes features on a criterion of frequency. We make the assumption that frequent links occur between sets of features that are themselves frequent. This property is used to reduce the search space and speed up the extraction process. We empirically show that it is well founded. We discuss the efficiency of the solution in terms of computation time and number of frequent patterns found depending on several frequency thresholds.
ISSN: 1947-8186

hal-00786166
https://hal.archives-ouvertes.fr/hal-00786166

Éditeur(s) : HAL CCSD
Résumé : International audience
In the area of the link mining, frequent pattern discovery tasks generally consist in the search for subgraphs frequently found in a network or a set of networks. Very recently, new axes of this problem has been proposed through the search for frequent links. Unlike traditional approaches that focus solely on structural regularities, frequent link mining methods exploit both the network structure and the attributes of nodes for extracting regularities in the links existing between node groups that share common characteristics. However, extracting frequent links is still a particularly challenging and computationally intensive issue since it is much dependent on the number of links. In this study, we propose a solution that is able to reduce the computing time by reducing the search to only a subset of of nodes. Experiments were conducted to understand the effects of different thresholds of the subset size on the loss of patterns and the gain in terms of computation time. Our solution proves to be efficient for a rather wide range of thresholds.
Research Challenges in Information Science
Vallence, Spain

hal-00767039
https://hal.archives-ouvertes.fr/hal-00767039
DOI : 10.1109/RCIS.2012.6240432

Éditeur(s) : HAL CCSD
Résumé : International audience
One of the most common tasks in the area of social network mining is the extraction of frequent patterns from social networks. Although traditional approaches have been mainly focused on subgraphs occurring frequently in a network or a set of networks, new approaches have attempted to exploit network structure and node properties in order to elicit new kinds of patterns. One of these news approaches is the extraction of conceptual links, a solution that combines both structure and node properties for providing knowledge on the groups of nodes the most connected in a social network. However, if the extraction of conceptual links offers a great potential in terms of knowledge discovery as well as network visualization, the search for these kinds of patterns remains a computationally intensive problem. Thus, the efficiency of the extraction processes highly depends on the efficiency of the underlying algorithm. In this paper, we focus on the extraction of maximal frequent conceptual links (MFCL) and we propose a hybrid algorithm that applies a filter on the nodes for reducing the search space to the most frequent groups of nodes. Although our solution potentially causes loss of some patterns, we demonstrate its efficiency by comparison with the MFCLMin algorithm. We investigate the potential loss of patterns, the gain on the runtime, and the gain on the number of comparisons.
IEEE International Conference on Research Challenges in Information Science
Paris, France

hal-00841699
https://hal.archives-ouvertes.fr/hal-00841699

Éditeur(s) : HAL CCSD Springer Verlag
Résumé : 17 pages, 11 figures.
International audience
The problem addressed in this paper is the automatic extraction of names from a document image. Our approach relies on the combination of two complementary analyses. First, the image-based analysis exploits visual clues to select the regions of interest in the document. Second, the textual-based analysis searches for name patterns and low-level word textual features. Both analyses are then combined at the word level through a neural network fusion scheme. Reported results on degraded documents such as facsimile and photocopied technical journals demonstrate the interest of the combined approach.
ISSN: 1433-7541

hal-00329459
https://hal.archives-ouvertes.fr/hal-00329459
DOI : 10.1007/s10044-006-0038-6

Éditeur(s) : HAL CCSD
Résumé : International audience
The extraction of knowledge from social networks is an area that has experienced significant growth in recent years. Indeed, thanks to the improvement of storage and calculation capacities, and the heterogeneity of data that can currently be extracted, much effort has been made to go beyond traditional knowledge, by proposing new kinds of patterns that take into account the context. However, while many works were interested in designing new patterns of knowledge or in optimizing existing approaches, few studies have been focused in merging patterns and on the useful knowledge emerging from such fusions. In this work, we focus on two network clustering approaches, able to extract two distinct kinds of patterns, and we seek to understand both the intersections that can exist between them and the knowledge that emerges from their fusion. The first is the classical nodes clustering approach that consists in searching for communities into a network. The second is the search for frequent conceptual links, a new link clustering approach that aims identifying frequent links between groups of nodes sharing common attributes. We propose a set of original measures that aim to evaluate the amount of shared information between these patterns when they are extracted from a same network. These measures are applied to three datasets and demonstrate the interest in simultaneously considering several sources of knowledge.
Advances in Knowledge Discovery and Management (AKDM)

hal-01514227
https://hal.archives-ouvertes.fr/hal-01514227
DOI : 10.1007/978-3-319-45763-5_13

Éditeur(s) : HAL CCSD Oxford University Press (OUP)
Résumé : International audience
Motivation: Gene fusion is an important evolutionary process. It can yield valuable information to infer the interactions and functions of proteins. Fused genes have been identified as non-transitive patterns of similarity in triplets of genes. To be computationally tractable, this approach usually imposes an a priori distinction between a dataset in which fused genes are searched for, and a dataset that may have provided genetic material for fusion. This reduces the `genetic space' in which fusion can be discovered, as only a subset of triplets of genes is investigated. Moreover, this approach may have a high-false-positive rate, and it does not identify gene families descending from a common fusion event. Results: We represent similarities between sequences as a network. This leads to an efficient formulation of previous methods of fused gene identification, which we implemented in the Python program FusedTriplets. Furthermore, we propose a new characterization of families of fused genes, as clique minimal separators of the sequence similarity network. This well-studied graph topology provides a robust and fast method of detection, well suited for automatic analyses of big datasets. We implemented this method in the C++ program MosaicFinder, which additionally uses local alignments to discard false-positive candidates and indicates potential fusion points. The grouping into families will help distinguish sequencing or prediction errors from real biological fusions, and it will yield additional insight into the function and history of fused genes.
ISSN: 1367-4803

hal-01544795
https://hal.archives-ouvertes.fr/hal-01544795
DOI : 10.1093/bioinformatics/btt049

Éditeur(s) : HAL CCSD
Résumé : International audience
Numerous social network mining methods have been proposed until now for addressing social mining tasks and specially searching for communities or frequent social patterns. However, the degree of complementarity of these methods has been very little studied. In this paper, we focus on two knowledge extraction processes in social networks: a link-based clustering that may extract social communities and a recent approach that searches for frequent conceptual link involving both clustering and search for frequent social patterns. We explore how the models extracted by each method may match and which potential useful knowledge they may provide. Our objective is to evaluate the potential relationships between communities and frequent conceptual links. For this purpose, we propose a set of measures for evaluating the degree to which these patterns extracted from the same dataset are matching. Our approach is applied on two datasets and demonstrates the importance of considering simultaneously various kinds of knowledge and their complementarity.
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Niagara falls, Canada

hal-00874351
https://hal.archives-ouvertes.fr/hal-00874351

Éditeur(s) : HAL CCSD
Résumé : International audience
In this article, we analyse a collaborative network to understand the underlying patterns that structure the co-writing process of scientific articles. Our goal is to identify and understand the collaboration tendencies from authors publishing activities. For this purpose, we adopt a descriptive modelling through a network approach that consists first in generating the collaborative network from data on publications. Nodes of the network are then enriched with a set of individual attributes extracted from the publishing activity of each author. Finally, we search for conceptual views, a recent link clustering approach, which allows to summarize any kind of networks by highlighting the sets of attributes found frequently linked. Results show that it exists strong tendencies that unconsciously structure the collaboration behaviours. In this paper, we present these tendencies and show how they evolve according to different extraction thresholds.
EEE/ACM International Conference on Advances in Social Networks Analysis and Mining
Sydney, Australia

hal-01637563
https://hal.archives-ouvertes.fr/hal-01637563
DOI : 10.1145/3110025.3110146

Éditeur(s) : HAL CCSD
Résumé : International audience
In the network modeling area, the most widely used definition of a "pattern" is that of a subgraph, a notion that considers only the network topological structure. While this definition has been very useful for extracting subgraphs frequently found in a network or a set of networks, it does not take into account the node attributes, an intrinsic component of social networks that often provides relevant information on the role or the position of a node in a network. In this paper, we propose a novel approach for extracting frequent patterns in social networks, called frequent link mining, based on the search for particular patterns that combine information on both network structure and node attributes. This kind of patterns, that we call frequent links, provides knowledge on the groups of nodes connected in the social network. In this article, we detail the method proposed for extracting frequent links and discuss its flexibility and its complexity. We demonstrate the efficiency of our solution by carrying out qualitative and quantitative studies.
Advances in Database (Weston, Conn.)s and Information Systems
Poznań, Poland

hal-00767050
https://hal.archives-ouvertes.fr/hal-00767050
DOI : 10.1007/978-3-642-33074-2_28

Éditeur(s) : HAL CCSD American Society for Biochemistry and Molecular Biology
Résumé : International audience
Neuroglobins, previously thought to be restricted to vertebrate neurons, were detected in the brain of a photosymbiotic acoel, Symsagittifera roscoffensis, and in neurosensory cells of the jellyfish Clytia hemisphaerica. For the neuroglobin of S. roscoffensis, a member of a lineage that originated either at the base of the bilateria or of the deuterostome clade, we report the ligand binding properties, crystal structure at 2.3 Å, and brain immunocytochemical pattern. We also describe in situ hybridizations of two neuroglobins specifically expressed in differentiating nematocytes (neurosensory cells) and in statocytes (ciliated mechanosensory cells) of C. hemisphaerica, a member of the early branching animal phylum cnidaria. In silico searches using these neuroglobins as queries revealed the presence of previously unidentified neuroglobin-like sequences in most metazoan lineages. Because neural systems are almost ubiquitous in metazoa, the constitutive expression of neuroglobin-like proteins strongly supports the notion of an intimate association of neuroglobins with the evolution of animal neural systems and hints at the preservation of a vitally important function. Neuroglobins were probably recruited in the first protoneurons in early metazoans from globin precursors. Neuroglobins were identified in choanoflagellates, sponges, and placozoans and were conserved during nervous system evolution. Because the origin of neuroglobins predates the other metazoan globins, it is likely that neuroglobin gene duplication followed by co-option and subfunctionalization led to the emergence of globin families in protostomes and deuterostomes (i.e. convergent evolution).
ISSN: 0021-9258

hal-01020584
http://hal.upmc.fr/hal-01020584
http://hal.upmc.fr/hal-01020584/document
http://hal.upmc.fr/hal-01020584/file/Rosko_jbc_revised.pdf
DOI : 10.1074/jbc.M112.407601

Éditeur(s) : HAL CCSD Elsevier
Résumé : International audience
These last years, many analysis methods have been proposed to extract knowledge from social networks. As for the traditional data mining domain, these network-based approaches can be classified according to two main families. The approaches based on predictive modelling, which encompass the techniques that analyse current and historical facts to make predictive assumptions about future or unknown events. The approaches based on descriptive modelling, which cover the set of techniques that aim to summarize the data by identifying some relevant features in order to describe how things organize and actually work. In this paper, we review the main descriptive modelling methods of social networks and show for each of them the resulting useful knowledge on a running example. We particularly emphasize on the most recent methods that combine information available on both the network structure and the node attributes in order to provide original description models taking into account the context.
EISSN: 1877-0509

hal-01312383
https://hal.univ-antilles.fr/hal-01312383
DOI : 10.1016/j.procs.2015.05.505

Éditeur(s) : HAL CCSD BioMed Central
Résumé : International audience
This study aims to assess the evidence on adverse pregnancy outcome associated with living close to polluted industrial sites, and identify the strengths and weaknesses of published epidemiological studies. A systematic literature search has been performed on all epidemiological studies published in developed countries since 1990, on the association between residential proximity to industrial sites (hazardous waste sites, industrial facilities and landfill sites) and adverse pregnancy outcome (low birth weight, preterm birth, small for gestational age, intrauterine growth retardation, infant mortality, congenital malformation). Based on 41 papers, our review reveals an excess risk of reproductive morbidity. However, no studies show significant excess risk of mortality including fetal death, neonatal or infant mortality and stillbirth. All published studies tend to show an increased risk of congenital abnormalities, yet not all are statistically significant. All but two of these studies revealed an excess risk of low birth weight. Results for preterm birth, small for gestational age and intrauterine growth retardation show the same pattern. There is suggestive evidence from the post-1990 literature that residential proximity to polluted sites (including landfills, hazardous waste sites and industrial facilities) might contribute to adverse reproductive outcomes, especially congenital malformations and low birth weight—though not mortality. This body of evidence has limitations that impede the formulation of firm conclusions, and new, well-focused studies are called for. The review findings suggest that continued strengthening of rules governing industrial emissions as well as industrial waste management and improved land use planning are needed.
ISSN: 1476-072X

Droits : http://creativecommons.org/licenses/by/
hal-01547817
http://hal.upmc.fr/hal-01547817
http://hal.upmc.fr/hal-01547817/document
http://hal.upmc.fr/hal-01547817/file/s12942-017-0091-y.pdf
DOI : 10.1186/s12942-017-0091-y

Éditeur(s) : HAL CCSD American Chemical Society
Résumé : International audience
The Chromosome-Centric Human Proteome Project (C-HPP) aims at cataloguing the proteins as gene products encoded by the human genome in a chromosome-centric manner. The existence of products of about 82% of the genes has been confirmed at the protein level. However, the number of so-called "missing proteins" remains significant. It was recently suggested that the expression of proteins that have been systematically missed might be restricted to particular organs or cell types, for example, the testis. Testicular function, and spermatogenesis in particular, is conditioned by the successive activation or repression of thousands of genes and proteins including numerous germ cell- and testis-specific products. Both the testis and postmeiotic germ cells are thus promising sites at which to search for missing proteins, and ejaculated spermatozoa are a potential source of proteins whose expression is restricted to the germ cell lineage. A trans-chromosome-based data analysis was performed to catalog missing proteins in total protein extracts from isolated human spermatozoa. We have identified and manually validated peptide matches to 89 missing proteins in human spermatozoa. In addition, we carefully validated three proteins that were scored as uncertain in the latest neXtProt release (09.19.2014). A focus was then given to the 12 missing proteins encoded on chromosomes 2 and 14, some of which may putatively play roles in ciliation and flagellum mechanistics. The expression pattern of C2orf57 and TEX37 was confirmed in the adult testis by immunohistochemistry. On the basis of transcript expression during human spermatogenesis, we further consider the potential for discovering additional missing proteins in the testicular postmeiotic germ cell lineage and in ejaculated spermatozoa. This project was conducted as part of the C-HPP initiatives on chromosomes 14 (France) and 2 (Switzerland). The mass spectrometry proteomics data have been deposited with the ProteomeXchange Consortium under the data set identifier PXD002367
ISSN: 1535-3893

hal-01187320
https://hal-univ-rennes1.archives-ouvertes.fr/hal-01187320
DOI : 10.1021/acs.jproteome.5b00170
PUBMED : 26168773

Éditeur(s) : HAL CCSD
Résumé : International audience
In this work, we propose a novel approach for the discovery of frequent patterns in a social network on the basis of both vertex attributes and link frequency. With an analogy to the traditional task of mining frequent item sets, we show that the issue addressed can be formulated in terms of a conceptual analysis that elicits conceptual links. A social-based conceptual link is a synthetic representation of a set of links between groups of vertexes that share similar internal properties. We propose a first algorithm that optimizes the search into the concept lattice of conceptual links and extracts maximal frequent conceptual links. We study the performances of our solution and give experimental results obtained on a sample example. Finally we show that the set of conceptual links extracted provides a conceptual view of the social network.
IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM)
Istanbul, Turkey

hal-00786161
https://hal.archives-ouvertes.fr/hal-00786161
DOI : 10.1109/ASONAM.2012.15

Éditeur(s) : HAL CCSD
Résumé : International audience
This paper proposes a new knowledge discovery method called FLMin to discover frequent patterns in a social network. The algorithm works without previous knowledge on the network and exploits both the structure and the attributes of nodes to extract regularities called Frequent Links. Unlike traditional works in this area that solely exploit structural regularities of the network, the originality of FLMin is its ability to gather these two kinds of information in the search for patterns. In this paper, we detail the method proposed for extracting frequent links and discuss its complexity and its flexibility. The efficiency of our solution is evaluated by conducting qualitative and quantitative studies for understanding how behaves FLMin according to different parameters.
Networked Digital Technologies
Dubai, United Arab Emirates

hal-00768431
https://hal.archives-ouvertes.fr/hal-00768431
DOI : 10.1007/978-3-642-30567-2_38

Éditeur(s) : HAL CCSD Springer
Résumé : International audience
he search for frequent conceptual links (FCL) is a new network clustering approach that exploits both the network structure and the node properties. While recent works have been focused on the optimisation of the FCL extraction, no study has been conducted on the matching or the intersections between the conceptual links and the classical clustering approach which consists in extracting communities. In this paper, we focus on these two approaches. Our objective is to evaluate the possible relationships existing between FCL and communities to understand how the patterns obtained by each kind of methods may match as well as the useful knowledge resulting from the intersections of these two kinds of knowledge. For this purpose, we propose a set of original measures, based on the notion of homogeneity, assessing the level of shared information between these patterns when they are extracted from the same dataset. The measures are applied on three datasets and demonstrate the importance of considering simultaneously various kinds of knowledge and their intersections.
ISSN: 1869-5450

hal-01312313
https://hal.archives-ouvertes.fr/hal-01312313
DOI : 10.1007/s13278-014-0197-1

Éditeur(s) : HAL CCSD INVS
Résumé : National audience
Context – Cervical cancer is the second most frequent cancer of women in French Guiana. Studies have shown that populations living in remote villages in the interior of the territory have early sexual relations and that multiple sexual partnerships are frequent. Hence, the main objective of the study was to determine the prevalence of Human Papilloma Virus (HPV) in these areas.Methods – This multicentric cross sectional study was conducted in women aged 20 to 65 years, living in theremote villages along the Maroni and Oyapock rivers. Women were included on a voluntary basis after beinginformed of the study team schedule through radio address and key opinion leaders.The search for HPV and cytologic examinations were performed on each sample. HPV infection was defined bythe detection of viral DNA using the Greiner Bio One® kit. Cytologic analyses were performed using the 2001Bethesda classification.Results – Overall, 643 women were included in the study. Age-standardized HPV prevalence was 35%. Theprevalence curve by age group showed a U-shaped pattern: women over 50 years had the highest risk of being infected by HPV, followed by women aged 20-29 years. In addition, 26.1% of women with a normal smear test had HPV infection. The most frequent genotypes were HPV52, HPV58, and HPV16. On interpretable smears 1.16% of women had high grade superficial intra-epithelial (HSIL) lesions.Conclusions – The standardized prevalence of HPV in French Guiana is among the highest in the world. HSILcytological lesions were nearly 4 times more frequent than in the Île-de-France region. Given the importance of the incidence of cervical cancer in French Guiana, these results suggest it may be preferable to use HPV testing than cytology. Vaccination against HPV, preferably with the new nonavalent vaccine seems an appropriate prevention measure. However, this intervention will be a challenge to implement in this region where a significant proportion of the population is not covered by health insurance.
Contexte – Le cancer du col de l’utérus est le deuxième cancer féminin le plus fréquent en Guyane française.Des études ont montré que les populations résidant dans les communes isolées de l’intérieur du départementdébutent leur vie sexuelle de façon précoce et que le multipartenariat sexuel y est fréquent. Dans ce contexte, l’objectif principal de cette étude était de déterminer la prévalence de l’infection à papillomavirus humains (HPV) dans ces zones.Méthodes – Cette étude transversale multicentrique a été conduite auprès des femmes âgées de 20 à 65 ansrésidant dans les communes isolées des fleuves Maroni et Oyapock. Les femmes étaient incluses sur la basedu volontariat après avoir été informées du passage de l’équipe de l’étude via la radio locale et par les leadersd’opinion. La recherche d’infection à HPV et les analyses cytologiques ont été réalisées sur chaque prélèvement. L’infection à HPV était définie par la détection d’ADN viral par le kit de dépistage Greiner Bio One®. Les analyses cytologiques ont été décrites selon la classification de Bethesda 2001.Résultats – Au total, 643 femmes ont été incluses. La prévalence de l’infection à HPV, standardisée sur l’âge,était de 35%. La courbe de prévalence par classe d’âge présentait une forme en U : les femmes de plus de50 ans avaient le plus haut risque d’être infectées par HPV, suivies par les femmes âgées de 20 à 29 ans.Par ailleurs, 26,1% des femmes ayant un frottis normal étaient infectées par le HPV. Les génotypes les plusfréquents étaient HPV52, HPV58 et HPV16. Sur les frottis interprétables, 1,16% des femmes avaient des lésions de haut grade (type HSIL).Conclusions – Le taux standardisé de prévalence de l’infection par le HPV en Guyane est parmi les plus élevésau monde. Les lésions cytologiques de type HSIL étaient près de 4 fois plus fréquentes qu’en Île-de-France.Étant donné l’importance de l’incidence du cancer du col de l’utérus en Guyane, ces résultats montrent qu’il est peut être préférable d’utiliser le test HPV plutôt que la cytologie. La vaccination anti-HPV, de préférence avec le nouveau vaccin nonavalent, semble être une mesure de prévention appropriée. Pour autant, cela reste un challenge de mettre en oeuvre ces interventions dans cette région où une part importante de la population n’a pas d’assurance maladie.
ISSN: 1953-8030

Droits : info:eu-repo/semantics/OpenAccess
inserm-01407222
http://www.hal.inserm.fr/inserm-01407222
http://www.hal.inserm.fr/inserm-01407222/document
http://www.hal.inserm.fr/inserm-01407222/file/2016%2C%20Dufit%20et%20al.pdf

Éditeur(s) : HAL CCSD Springer
Résumé : International audience
Traditional network generation models aim to replicate global structural properties observed on various real-world networks through synthetic link formation mechanisms such as triadic closure or preferential attachment. Nowadays, the large amount of data available allow to study more precisely the link formation processes and to compare models with real situations. In this work, we analyze the network formed by the communication activities of the users of a telephony operator for studying the link formation process. Our goal is to identify the underlying formation mechanisms and checking if they match those proposed in traditional models. Indeed, the communications emitted and received by users are strong indicators for understanding the underlying patterns of the link formation process and highlighting how some individual properties induce the formation process in such a network. In a first study conducted at a global level, we show that the traditional mechanisms commonly used in network generation models cannot reproduce alone the link formation in this network. In a second study, we adopt a new point of view and analyze locally the link formation process by searching for correlations between some user attributes and the formation of the new links. The results obtained show that a very strong percentage of new links are formed between individuals with strong similarity.
ISSN: 1869-5450

hal-01312310
https://hal.univ-antilles.fr/hal-01312310
DOI : 10.1007/s13278-015-0304-y