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This is the KONECT project, a project in the area of network science with the goal to collect network datasets, analyse them, and make available all analyses online. KONECT stands for Koblenz Network Collection, as the project has roots at the University of Koblenz–Landau in Germany. All source code is made available as Free Software, and includes a network analysis toolbox for GNU Octave, a network extraction library, as well as code to generate these web pages, including all statistics and plots. KONECT contains over a hundred network datasets of various types, including directed, undirected, bipartite, weighted, unweighted, signed and rating networks. The networks of KONECT are collected from many diverse areas such as social networks, hyperlink networks, authorship networks, physical networks, interaction networks and communication networks. The KONECT project has developed network analysis tools which are used to compute network statistics, to draw plots and to implement various link prediction algorithms. The result of these analyses are presented on these pages. Whenever we are allowed to do so, we provide a download of the networks.
<<<!!!<<< This repository is no longer available. >>>!!!>>> TeachingWithData.org is a portal where faculty can find resources and ideas to reduce the challenges of bringing real data into post-secondary classes. It allows faculty to introduce and build students' quantitative reasoning abilities with readily available, user-friendly, data-driven teaching materials.
!!! >>> the repository is offline, data can be found here: https://osf.io/gjp53/ <<< !!! Our lab investigates how cognition manifests in, and is influenced by, the social contexts in which it occurs. We focus: 1) on how conversational interactions can reshape memory, by promoting shared remembering and shared forgetting, and 2) on how socio-cognitive processes affect the formation of collective memories and beliefs, and the dynamics of collective decisions. In exploring these issues, while maintaining high ecological validity, our lab integrates a wide range of methodologies, including laboratory experiments, field studies, social network analysis, and agent-based simulations.
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Created in 2005 by the CNRS, CNRTL unites in a single portal, a set of linguistic resources and tools for language processing. The CNRTL includes the identification, documentation (metadata), standardization, storage, enhancement and dissemination of resources. The sustainability of the service and the data is guaranteed by the backing of the UMR ATILF (CNRS - Université Nancy), support of the CNRS and its integration in the excellence equipment project ORTOLANG .
OpenML is an open ecosystem for machine learning. By organizing all resources and results online, research becomes more efficient, useful and fun. OpenML is a platform to share detailed experimental results with the community at large and organize them for future reuse. Moreover, it will be directly integrated in today’s most popular data mining tools (for now: R, KNIME, RapidMiner and WEKA). Such an easy and free exchange of experiments has tremendous potential to speed up machine learning research, to engender larger, more detailed studies and to offer accurate advice to practitioners. Finally, it will also be a valuable resource for education in machine learning and data mining.