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Neural Collaborative Filtering [PDF]
The Web Conference, 2017 In recent years, deep neural networks have yielded immense success on speech recognition, computer vision and natural language processing. However, the exploration of deep neural networks on recommender systems has received relatively less scrutiny.
Xiangnan He +5 more
semanticscholar +3 more sources
Improving Graph Collaborative Filtering with Neighborhood-enriched Contrastive Learning [PDF]
The Web Conference, 2022 Recently, graph collaborative filtering methods have been proposed as an effective recommendation approach, which can capture users’ preference over items by modeling the user-item interaction graphs.
Zihan Lin +3 more
semanticscholar +1 more source
Frontiers in Education, 2021 This research work explored how collaborative, whole-body exhibits affect science learning in informal out-of-school settings. Specifically, the study investigated how exhibit features guided visitors to engage actively in experiential exploration of the
Marianne Lykke +2 more
doaj +1 more source
International Journal of Health Services Research and Policy, 2022 Interprofessional cooperation and teamwork among health professionals in the health care system are crucial for improving patient satisfaction and quality of health services.
Gora Miljanovic +6 more
doaj +1 more source
MetaGPT: Meta Programming for Multi-Agent Collaborative Framework
arXiv.org, 2023 Recently, remarkable progress has been made in automated task-solving through the use of multi-agent driven by large language models (LLMs). However, existing LLM-based multi-agent works primarily focus on solving simple dialogue tasks, and complex tasks
Sirui Hong +11 more
semanticscholar +1 more source
DETRs with Collaborative Hybrid Assignments Training [PDF]
IEEE International Conference on Computer Vision, 2022 In this paper, we provide the observation that too few queries assigned as positive samples in DETR with one-to-one set matching leads to sparse supervision on the encoder’s output which considerably hurt the discriminative feature learning of the ...
Zhuofan Zong, Guanglu Song, Yu Liu
semanticscholar +1 more source
Neural Graph Collaborative Filtering [PDF]
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2019 Learning vector representations (aka. embeddings) of users and items lies at the core of modern recommender systems. Ranging from early matrix factorization to recently emerged deep learning based methods, existing efforts typically obtain a user's (or ...
Xiang Wang +4 more
semanticscholar +1 more source
Collaborative management: a sustainable natural tourism development model
Jurnal Pariwisata Pesona, 2022 In the development of natural tourism areas in the Sirah Kencong Tourism Area, the regional government of Blitar Regency, East Java Province has made various efforts and efforts. However, this effort still has some obstacles in its implementation.
Fitria Earlike Anwar Sani +1 more
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Hypergraph Contrastive Collaborative Filtering [PDF]
Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, 2022 Collaborative Filtering (CF) has emerged as fundamental paradigms for parameterizing users and items into latent representation space, with their correlative patterns from interaction data.
Lianghao Xia +5 more
semanticscholar +1 more source
IEEE Access, 2020 Robotic exploration of wide terrains, such as agricultural fields, could be challenging while considering the limited robot's capabilities in terms of sensing and power.
Mohamed G. B. Atia +2 more
doaj +1 more source