Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Tongrang, Fan"'
Publikováno v:
International Journal on Semantic Web and Information Systems. 18:1-17
In recent years, the related research of entity alignment has mainly focused on entity alignment via knowledge embeddings and graph neural networks; however, these proposed models usually suffer from structural heterogeneity and the large-scale probl
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 15 (2019)
Currently, large data sets are deployed on large-scale clusters, which require a large amount of physical resources. However, current network architecture does not have flexible deployment, making it difficult to adjust physical resources after deplo
Externí odkaz:
https://doaj.org/article/9f5ea3e20cdc42c1bb0426fdf3a39a8a
Publikováno v:
International Journal of Distributed Sensor Networks, Vol 15 (2019)
With the development of science and technology, the interactions among scientific research teams become more and more frequent, and their relationship and behavior become more and more complex. Many researches mainly adopt complex network to analyze,
Externí odkaz:
https://doaj.org/article/003f60ca6cd34ac18895bb49fdde70ce
Publikováno v:
Neural Computing and Applications.
Publikováno v:
Journal of Ambient Intelligence and Humanized Computing; 20240101, Issue: Preprints p1-10, 10p
Publikováno v:
Pattern Recognition Letters. 144:54-60
With the increasing complexity of scientific research, it has gradually turned to a collaborative approach, which can promote knowledge sharing, resource sharing and improve the efficiency of scientific research achievements. Therefore, It is of grea
Publikováno v:
Soft Computing.
Publikováno v:
Computing.
Data reuse strategy is an effective method to save storage space and improve data utilization in data management. In view of the successful application of deep learning in the field of text mining, a data reuse strategy based on deep learning is prop
Publikováno v:
Wireless Personal Communications. 102:2759-2774
The data analysis is closely related to data attribute dimension. The traditional extraction and partition of data attribute dimension is so manual and inefficiency as to not meet the needs of analysing big data. This paper proposed an attribute dime
Publikováno v:
International Journal of Control and Automation. 9:199-210