Sang-min Lee, Namgi Kim*
CMC-Computers, Materials & Continua, Vol.78, No.2, pp. 1897-1914, 2024, DOI:10.32604/cmc.2023.046346
Abstract Recommendation Information Systems (RIS) are pivotal in helping users in swiftly locating desired content from the vast amount of information available on the Internet. Graph Convolution Network (GCN) algorithms have been employed to implement the RIS efficiently. However, the GCN algorithm faces limitations in terms of performance enhancement owing to the due to the embedding value-vanishing problem that occurs during the learning process. To address this issue, we propose a Weighted Forwarding method using the GCN (WF-GCN) algorithm. The proposed method involves multiplying the embedding results with different weights for each hop layer during graph learning. By applying the WF-GCN… More >
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