La description :The statistical AI algorithm to analyze communication networks allows you to cluster the nodes of networks with textual edges while identifying topics which are used in communications. You can analyze...
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L'adresse IP principale: 193.49.116.47,Votre serveur France,Paris
ISP:U.F.R. de Mathematiques et Informatique TLD:fr Code postal:fr
Ce rapport est mis à jour en 01-Aug-2020
Created Date:
2017-03-31
Changed Date:
2020-03-30
Expires Date:
2023-03-31
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Notre service GeoIP a trouvé l'hôte linkage.fr.Actuellement, hébergé dans France et son fournisseur de services est U.F.R. de Mathematiques et Informatique .
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The statistical AI algorithm to analyze communication networks allows you to cluster the nodes of networks with textual edges while identifying topics which are used in communications. You can analyze with networks such as email networks or co-authorship networks. allows you to upload your own network data or to make requests on scientific databases (Arxiv, Pubmed, HAL). Try Blog posts March 27, 2019 Pi Day and visit of Jean-Michel Blanquer and Antoine Petit June 26, 2018 Commercial brochure and licensing June 1, 2018 Data challenge : weak signal detection April 10, 2018 An introduction video to Feb. 6, 2018 The press talks about ... July 27, 2017 L’analyse textuelle de réseaux, Qu’est-ce que c’est ? Comment faire ? (par Muriel Epstein) June 20, 2017 A deeper analysis of the Enron Scandal (by Charles Bouveyron) June 7, 2017 Importing your own dataset - Example with Reddit comments June 6, 2017 Tip: Labeling your clusters and topics June 6, 2017 Spacialize and view your result in Gephi June 2, 2017 How to analyse a co-authorship network in How does work ? is built upon a sound statistical model for networks with textual edges and implement an innovative and efficient inference algorithm to fit the model on your data. Model selection allows to find in a fully automatic way the best number of groups and topics. Upload and manage your data securely Upload all or part of your data on the platform to analyze them with . You will keep full control on the data you upload and only you will be able to access them. Focus on data and interpretation Minimum configuration is required to use since it selects the most sensible parameters for the data you provide. No scientific background is required to start working and get results. Advanced configuration options are also available if you need specific setups. Visualize and export the results also provides advanced visualization tools, based on the specific features of the statistical modeling. finally allows to export as CSV files the clustering results obtained on your data for further processing. The statistical method behind the platform The methodology implemented is partly related to an article published in the journal « Statistics and Computing ». The reference to cite in case of academic use of the platform is « C. Bouveyron, P. Latouche and R. Zreik, The Stochastic Topic Block Model for the Clustering of Networks with Textual Edges, Statistics and Computing, in press, 2017. DOI: 10.1007/s11222-016-9713-7 ». The people behind is developed by an academic team: Methodology and code: C. Bouveyron and P. Latouche Web interface and visualizations: D. Marié Terms and conditions Credits
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