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Titlebook: Complex Networks & Their Applications IX; Volume 2, Proceeding Rosa M. Benito,Chantal Cherifi,Marta Sales-Pardo Conference proceedings 2021

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A Sentiment Enhanced Deep Collaborative Filtering Recommender System Additionally, the CNN learns the specific review of users and his sentiments aspects. Hence, it models accurately the item latent factors and creates a profile model for each user. The proposed framework allows users to find suitable items through the comprehensive aggregation of user’s preferences
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Stability of Elastic Structures structure. Using synthetic data, we first confirm the effectiveness of the inference method and the validity of the approximation formula. Using real data of Location-Based Social Networks (LBSNs), we demonstrate the significance of the RH model in terms of predicting the future events, and uncover
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Stability of Elastic Structuress of a network. For the computation of consensus embeddings, we use linear (singular value decomposition) and non-linear (variational auto-encoder) dimensionality reduction methods. Our results on a large selection of protein-protein interaction (PPI) networks (eight versions with 255 potential comb
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https://doi.org/10.1007/978-1-4614-8477-6ine-learning model on the snapshots and apply this model to the real-word network to find the best BI parameters. We apply these parameters to the sampled real-world network to measure the quality of the sets of initiators found this way. We use various real-world networks to validate our approach a
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Stability of Linear Periodic Equationsion of the layers of the reference networks. To the best of our knowledge, this is the first study that provides a systematic comparison of generative models for airline transportation multilayer networks.
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