Zobrazeno 1 - 10
of 53
pro vyhledávání: '"Suqi Zhang"'
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 11, Pp 19209-19231 (2023)
In order to capture the complex dependencies between users and items in a recommender system and to alleviate the smoothing problem caused by the aggregation of multi-layer neighborhood information, a multi-behavior recommendation model (DNCLR) based
Externí odkaz:
https://doaj.org/article/30fb8fee4155465090f8e021455ddfe1
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 9, Pp 16401-16420 (2023)
In order to solve the problem of timeliness of user and item interaction intention and the noise caused by heterogeneous information fusion, a recommendation model based on intention decomposition and heterogeneous information fusion (IDHIF) is propo
Externí odkaz:
https://doaj.org/article/61177258e4d9481fbe656c268818388f
Publikováno v:
Mathematical Biosciences and Engineering, Vol 20, Iss 6, Pp 9670-9692 (2023)
Social relations can effectively alleviate the data sparsity problem in recommendation, but how to make effective use of social relations is a difficulty. However, the existing social recommendation models have two deficiencies. First, these models a
Externí odkaz:
https://doaj.org/article/41868ebffabe4c5ab7724a892271f82f
Publikováno v:
Entropy, Vol 25, Iss 10, p 1388 (2023)
Social recommender systems are expected to improve recommendation quality by incorporating social information when there is little user–item interaction data. Therefore, how to effectively fuse interaction information and social information becomes
Externí odkaz:
https://doaj.org/article/f5f2a8604838424ab04ccc74e2df75e5
Publikováno v:
IEEE Access, Vol 8, Pp 39078-39090 (2020)
Identification of community structures is essential for characterizing and analyzing complex networks. Having focusing primarily on network topological structures, most existing methods for community detection ignore two types of non-topological rela
Externí odkaz:
https://doaj.org/article/e612b23a9277424ea7c0317f5df25006
Publikováno v:
Energies, Vol 15, Iss 23, p 9197 (2022)
Accurate load forecasting is conducive to the formulation of the power generation plan, lays the foundation for the formulation of quotation, and provides the basis for the power management system and distribution management system. This study aims t
Externí odkaz:
https://doaj.org/article/470c537b47c84ab3a6153ea0810e1297
Publikováno v:
Applied Sciences, Vol 12, Iss 23, p 12141 (2022)
Social recommendation has received great attention recently, which uses social information to alleviate the data sparsity problem and the cold-start problem of recommendation systems. However, the existing social recommendation methods have two defic
Externí odkaz:
https://doaj.org/article/7a38faffbedc4edb961e5bf7503454d1
Publikováno v:
Applied Sciences, Vol 12, Iss 17, p 8764 (2022)
The existing recommendation model based on a knowledge graph simply integrates the behavior features in a user–item bipartite graph and the content features in a knowledge graph. However, the difference between the two feature spaces is ignored. To
Externí odkaz:
https://doaj.org/article/b041a821d3ee4f668950f6a28d78c17d
Publikováno v:
Applied Sciences, Vol 12, Iss 15, p 7434 (2022)
The recommendation model based on the knowledge graph (KG) alleviates the problem of data sparsity in the recommendation to a certain extent and further improves the accuracy, diversity, and interpretability of recommendations. Therefore, the knowled
Externí odkaz:
https://doaj.org/article/912456916d9444889c592763aa92b858
Publikováno v:
PLoS ONE, Vol 10, Iss 9, p e0138682 (2015)
Edge-preserving image smoothing is one of the fundamental tasks in the field of computer graphics and computer vision. Recently, L0 gradient minimization (LGM) has been proposed for this purpose. In contrast to the total variation (TV) model which em
Externí odkaz:
https://doaj.org/article/d4706b5721b04264aef4b35268d3833f