Keyword Search of Incomplete Graph Based on Kernel Principal Component Analysis
Yan Zhang, Mingli Jing · 2023
In the keyword search problem, the incomplete graph situation is a unavoidable role. Aiming at the incomplete graph situation that is not fully considered in the existing methods, a keyword search method for incomplete graphs based on kernel principal component analysis is proposed. First, the dimension reduction of the feature vector is carried out through the kernel function; then, the keyword feature vector is extracted through KPCA; finally, all the feature vectors are sorted to obtain the final keyword search result. The experimental results show that the proposed method achieves high accuracy in keyword search with less running time; compared with other algorithms, the proposed method has better performance in terms of recall and precision.