Fuzzy-Constrained Graph Patter n Matching in Medical Knowledge Graphs

he research on graph pattern matching (GPM) has attracted a lot of attention. However, most of theresearch has focused on complex networks, and there are few researches on GPM in the medical field.Hence, with GPM this paper is to make a breast cancer-oriented diagnosis before the surgery. Technically,this paper has firstly made a new definition of GPM, aiming to explore the GPM in the medical field,especially in Medical Knowledge Graphs (MKGs). Then, in the specific matching process, this paperintroduces fuzzy calculation, and proposes a multi-threaded bidirectional routing exploration (M-TBRE)algorithm based on depth first search and a two-way routing matching algorithm based on multi-threading.In addition, fuzzy constraints are introduced in the M-TBRE algorithm, which leads to the Fuzzy-M-TBREalgorithm. The experimental results on the two datasets show that compared with existing algorithms, ourproposed algorithm is more efficient and effective.