Titlebook: Handbuch Mitarbeiterkommunikation; Interne Kommunikatio Sabine Einwiller,Sonja A. Sackmann,Ansgar Zerfaß Living reference work 20200th edit

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Berend Barkela,Isabella Glogger,Michaela Maier,Frank M. Schneideral methods use the path-length between concepts in the ontology to calculate their semantic similarity. However, this simple method cannot present semantic relationship among concepts well. This study seeks to learn the concept embeddings in ontology, and then use the cosine similarity of two embedd

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Siegfried Schicks. The algorithm utilizes the graph attention mechanism to refresh embeddings efficiently, in which each update associate with local information only. To address the missing data, which is a common phenomenon in real-world networks, we model the auxiliary side information to capture more information

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Stephan Kaiser encoding pairwise constraints into spectral clustering. Essentially, the existing CSC algorithms coarsely lie in two camps in terms of encoding pairwise constraints: (1) they modify the original similarity matrix to encode pairwise constraints; (2) they regularize the spectral embedding to encode p

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Carolin Fleischmann, and models with a large number of parameters usually demand substantial computational resources, resulting in slower reasoning processes. In this paper, we propose a novel architecture for efficient recognition based on LSTM-Autoencoder and attention mechanism to address these challenges. Experime

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Christian Schwägerlney, Australia in February 2022.*.The 26 full papers presented together with 35 short papers were carefully reviewed and selected from 116 submissions. The papers were organized in topical sections in Part II named: Pattern mining; Graph mining; Text mining; Multimedia and time series data mining; a