Zobrazeno 1 - 10
of 29
pro vyhledávání: '"Nengjun Zhu"'
Publikováno v:
Journal of Social Computing, Vol 4, Iss 2, Pp 112-124 (2023)
Session-based recommender systems are increasingly applied to next-item recommendations. However, existing approaches encode the session information of each user independently and do not consider the interrelationship between users. This work is base
Externí odkaz:
https://doaj.org/article/cb39746fc69643239705292654530c9d
Publikováno v:
International Journal of Computational Intelligence Systems, Vol 15, Iss 1, Pp 1-10 (2022)
Abstract Resource constraints, e.g., limited product inventory or financial strength, may affect consumers’ choices or preferences in some recommendation tasks but are usually ignored in previous recommendation methods. In this paper, we aim to min
Externí odkaz:
https://doaj.org/article/9b9de3df81a648e282243845f002f3ad
Publikováno v:
Big Data Mining and Analytics, Vol 3, Iss 1, Pp 29-40 (2020)
To protect consumers and those who manufacture and sell the products they enjoy, it is important to develop convenient tools to help consumers distinguish an authentic product from a counterfeit one. The advancement of deep learning techniques for fi
Externí odkaz:
https://doaj.org/article/cbdcfb44a9c3484eb54dd9e80f37951b
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 17:1-22
A session-based recommendation system (SRS) tries to predict the next possible choice of anonymous users. In recent years, graph neural network (GNN) models have been successfully applied to SRSs and have achieved great success. Using GNN models in S
Predicting a Person’s Next Activity Region with a Dynamic Region-Relation-Aware Graph Neural Network
Autor:
Nengjun Zhu, Jian Cao, Xinjiang Lu, Chuanren Liu, Hao Liu, Yanyan Li, Xiangfeng Luo, Hui Xiong
Publikováno v:
ACM Transactions on Knowledge Discovery from Data. 16:1-23
The understanding of people’s inter-regional mobility behaviors, such as predicting the next activity region (AR) or uncovering the intentions for regional mobility, is of great value to public administration or business interests. While there are
Publikováno v:
Concurrency and Computation: Practice and Experience.
Publikováno v:
Computer Supported Cooperative Work and Social Computing ISBN: 9789819923847
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::9c5bb6c6141b19cebbcff8700e75089e
https://doi.org/10.1007/978-981-99-2385-4_2
https://doi.org/10.1007/978-981-99-2385-4_2
Social media is a crucial way to release information in a timely manner during disasters, which provides help to people who suffer from disasters. In this disaster information, each message may contain multiple labels. The single-label classification
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ccc7a7cf81c110c92631ccc93c41f94c
https://hdl.handle.net/10453/167889
https://hdl.handle.net/10453/167889
Publikováno v:
Proceedings of the 45th International ACM SIGIR Conference on Research and Development in Information Retrieval.
Publikováno v:
World Wide Web. 24:375-396
Pointwise prediction and Learning to Rank (L2R) are two hot strategies to model user preference in recommender systems. Currently, these two types of approaches are often considered independently, and most existing efforts utilize them separately. Un