Zobrazeno 1 - 10
of 913
pro vyhledávání: '"ZHU Yanmin"'
Publikováno v:
Nantong Daxue xuebao. Ziran kexue ban, Vol 20, Iss 3, Pp 49-56 (2021)
Aiming at determining the monitoring stations with strong spatial correlation, a method based on the K-means clustering algorithm for dividing the air quality monitoring stations is proposed. With Nantong as an example,the historical pollutant data i
Externí odkaz:
https://doaj.org/article/f53db909f5774966ab6872f564df9ad6
Autor:
Zhu, Yanmin, Tadesse, Loza F.
Spectroscopy is a powerful analytical technique for characterizing matter across physical and biological realms1-5. However, its fundamental principle necessitates specialized instrumentation per physical phenomena probed, limiting broad adoption and
Externí odkaz:
http://arxiv.org/abs/2407.16094
Autor:
Liu, Haobing, Ding, Jianyu, Zhu, Yanmin, Tang, Feilong, Yu, Jiadi, Jiang, Ruobing, Guo, Zhongwen
Publikováno v:
Knowledge-Based Systems 2023
Multi-behavioral sequential recommendation has recently attracted increasing attention. However, existing methods suffer from two major limitations. Firstly, user preferences and intents can be described in fine-grained detail from multiple perspecti
Externí odkaz:
http://arxiv.org/abs/2309.14938
Deep learning-based recommender systems have achieved remarkable success in recent years. However, these methods usually heavily rely on labeled data (i.e., user-item interactions), suffering from problems such as data sparsity and cold-start. Self-s
Externí odkaz:
http://arxiv.org/abs/2303.09902
Publikováno v:
IEEE TBD 2023
Behavior prediction based on historical behavioral data have practical real-world significance. It has been applied in recommendation, predicting academic performance, etc. With the refinement of user data description, the development of new function
Externí odkaz:
http://arxiv.org/abs/2207.11776
Deep neural network based recommendation systems have achieved great success as information filtering techniques in recent years. However, since model training from scratch requires sufficient data, deep learning-based recommendation methods still fa
Externí odkaz:
http://arxiv.org/abs/2206.04415
Traditional recommendation systems are faced with two long-standing obstacles, namely, data sparsity and cold-start problems, which promote the emergence and development of Cross-Domain Recommendation (CDR). The core idea of CDR is to leverage inform
Externí odkaz:
http://arxiv.org/abs/2108.03357
Publikováno v:
In Information Sciences March 2024 662
Publikováno v:
ACM TKDD 2022
Prediction tasks about students have practical significance for both student and college. Making multiple predictions about students is an important part of a smart campus. For instance, predicting whether a student will fail to graduate can alert th
Externí odkaz:
http://arxiv.org/abs/2103.13565
Publikováno v:
In Measurement 15 February 2024 225