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ClusPath: a temporal-driven clustering to infer typical evolution paths.

, , , and . Data Min. Knowl. Discov., 30 (5): 1324-1349 (2016)

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Overview and Preliminary Results for a Opinions Summarizarion Method., , and . CSCS, page 218-224. IEEE, (2013)A combination of opinion mining and social network techniques for discussion analysis., , and . Fouille de Données d'Opinions, volume E-17 of RNTI, Cépaduès-Éditions, (2009)Explainable Clustering via Exemplars: Complexity and Efficient Approximation Algorithms., , , , , and . CoRR, (2022)How to Use Temporal-Driven Constrained Clustering to Detect Typical Evolutions., , and . Int. J. Artif. Intell. Tools, (2014)Behavioral differences: insights, explanations and comparisons of French and US Twitter usage during elections., , , and . Soc. Netw. Anal. Min., 10 (1): 6 (2020)How to Use Temporal-Driven Constrained Clustering to Detect Typical Evolutions., , and . CoRR, (2016)Multivariate Powered Dirichlet Hawkes Process., , and . CoRR, (2022)Shallow Text Clustering Does Not Mean Weak Topics: How Topic Identification Can Leverage Bigram Features., , and . DMNLP@PKDD/ECML, volume 1646 of CEUR Workshop Proceedings, page 25-32. CEUR-WS.org, (2016)Dynamic Gaussian Embedding of Authors., , , and . WWW, page 2109-2119. ACM, (2022)Etude de l'image de marque d'entités dans le cadre d'une plateforme de veille sur le Web social., , , , , and . TALN (Demos), page 10-11. ATALA, (2015)