Securing Private Keys in Electronic Health Records Using Session-Based Hierarchical Key Encryption
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DOI: 10.1080/19361610.2017.1354272
Abstract: ABSTRACT Patients want the assurance that the confidentiality of their records accessed through Electronic Health Records (EHR) are safe. With increasing implementation of EHR for health care, privacy concern remains a barrier that limits patients'… read more here.
Keywords: based hierarchical; hierarchical key; session based; health ... See more keywords
Learning Sequential General Pattern and Dependency via Hybrid Neural Model for Session-Based Recommendation
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DOI: 10.1109/access.2022.3201244
Abstract: Recent study shows that recommendation system not only relys on user’s static preference, but also dynamic preference. Consequently, it leads to the emergence of session-based recommendation. With the development of recurrent neural network, this kind… read more here.
Keywords: based recommendation; recommendation; dependency; session based ... See more keywords
A Graph Positional Attention Network for Session-Based Recommendation
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DOI: 10.1109/access.2023.3235353
Abstract: The main idea of a session-based recommendation system is to model the user’s historical click sequence and then summarize user preferences and predict the items the user will interact with. The session recommendation model based… read more here.
Keywords: recommendation; session based; attention; model ... See more keywords
Attention-Enhanced Graph Neural Networks With Global Context for Session-Based Recommendation
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DOI: 10.1109/access.2023.3254897
Abstract: Session-based recommendation is a crucial task aiming to predict users’ interested items based only on anonymous user behaviors. Most recent solutions for session-based recommendation comprehensively consider the interactive information of all sessions but bring the… read more here.
Keywords: recommendation; session based; attention enhanced; session ... See more keywords
Self-Supervised Enhancement Method for Multi-Behavior Session-Based Recommendation
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DOI: 10.1109/access.2024.3504496
Abstract: Session-Based Recommendation(SBR) aims to capture users’ short-term and dynamic preferences through anonymous sessions. Most existing SBR methods neglect the collaborative information between multiple behaviors in a session when modeling user preferences, and they often struggle… read more here.
Keywords: method; self supervised; based recommendation; session ... See more keywords
PRIDES: A Probabilistic Model for Recurrent User Interest Drift Identification in Session-Based Recommendation
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DOI: 10.1109/access.2025.3564460
Abstract: A Session-Based Recommendation (SBR) identifies correlations among session interactions to understand user preferences and generate appropriate recommendations. A key challenge in this context is the dynamic change in user preferences, particularly when preferences disappear and… read more here.
Keywords: ruid; session; identification; based recommendation ... See more keywords
Hybrid-Order Gated Graph Neural Network for Session-Based Recommendation
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DOI: 10.1109/tii.2021.3091435
Abstract: Considering sessions as directed subgraphs, graph neural networks (GNNs) are supposed to be capable of capturing the complex dependencies among items and suitable for session-based recommendation. However, deep GNNs suffer from the oversmoothing problem of… read more here.
Keywords: hybrid order; based recommendation; session based;
Multi-Behavior Hypergraph Contrastive Learning for Session-Based Recommendation
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DOI: 10.1109/tkde.2024.3523383
Abstract: Most current session-based recommendations model session sequences solely based on the user's target behavior, ignoring the user's hidden preferences in auxiliary behaviors. Additionally, they use ordinary graphs to model one-to-one item correlations in the current… read more here.
Keywords: session representation; multi behavior; session; contrastive learning ... See more keywords
Enhancing Session-Based Recommendation With Multi-Interest Hyperbolic Representation Networks
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DOI: 10.1109/tnnls.2024.3502769
Abstract: Session-based recommendation (SBR) aims to predict the next item a user might click within an ongoing session, without relying on user profiles or historical data. Modern approaches typically use graph networks to learn item embeddings… read more here.
Keywords: representation; multi interest; session; based recommendation ... See more keywords
Skip-Gram and Transformer Model for Session-Based Recommendation
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DOI: 10.3390/app14146353
Abstract: Session-based recommendation uses past clicks and interaction sequences from anonymous users to predict the next item most likely to be clicked. Predicting the user’s subsequent behavior in online transactions becomes a problem mainly due to… read more here.
Keywords: skip gram; session; model; transformer ... See more keywords
Attention-Enhanced Graph Neural Networks for Session-Based Recommendation
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DOI: 10.3390/math8091607
Abstract: Session-based recommendation, which aims to match user needs with rich resources based on anonymous sessions, nowadays plays a critical role in various online platforms (e.g., media streaming sites, search and e-commerce). Existing recommendation algorithms usually… read more here.
Keywords: recommendation; based recommendation; session based; session ... See more keywords