Maximum Similarity Directed Subgraph Searching Algorithm on Subjective Logic
Zhou Hongwei, Zhipeng Ke, Zhang Yuchen, Yuan Jinhui, Huang Jinming · 2021 IEEE International Conference on Data Science and Computer Application (ICDSCA) · 2021
The determination of similar subgraphs has always been a difficult point in the search of directed graphs. Existing algorithms are difficult to accurately describe the similarity of subgraphs. Therefore, we proposes a novel search algorithm for maximal similar directed subgraph based on subjective logic. The algorithm is based on isomorphic nodes, based on the similarity argument of subjective logic for graphics containing a few nodes, greedy algorithm is adopted to gradually expand the scale of similar subgraphs until it is lower than the preset threshold. Compared with other related algorithms, this algorithm makes use of subjective logic’s ability to accurately describe realistic arguments and uncertain reasoning, which makes the judgment of subgraph similarity more accurate.