Covariance Projection as a General Framework of Data Fusion and Outlier Removal

Lee, Sukhan; Bakr, Muhammad Abu

doi:10.1007/978-3-319-90509-9_1

Cited by 1 publication

(1 citation statement)

References 13 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Bringing the results of the Canopy algorithm into the next precise clustering algorithm can greatly reduce the number of iterations of the clustering algorithm, thereby improving the efficiency and accuracy of the clustering. It can also reduce the probability of local optimal solutions to a certain extent [17,18]. Canopy's algorithm mechanism also determines that it has better performance for high-dimensional data processing [10].…”

Section: Canopy Algorithmmentioning

confidence: 99%

Visualization Research of College Students’ Career Planning Paths Integrating Deep Learning and Big Data

Guo

Liu

2022

Mathematical Problems in Engineering

View full text Add to dashboard Cite

As China’s education enters a high-level stage, more and more students graduate from Chinese colleges and universities. In particular, the current employment environment is flexible and multilateral, and there are more and more opportunities to choose from. In view of this situation, this article aims to visualize the career planning (CP) path of college students, so as to help college students adapt to the environment of flexible employment. For deep learning and big data (DLBA) technology, this article proposes the LSTM-Canopy algorithm, which is added to the traditional Canopy algorithm to enhance the self-learning clustering ability of the algorithm. Also, this study applies this algorithm to the visualization system of college students’ CP path, which can effectively improve the analysis and judgment of experts on career. The experiments in this article have proved that the system can meet the normal use of 400–500 users, and the system server has successfully passed 40 load tests, and the running time is also less than 2.5s, which proves the reliability of the system.

show abstract

Section: Canopy Algorithmmentioning

confidence: 99%