The present disclosure provides an object identification method, which can be applied to the field of
artificial intelligence and
big data, and includes: converting
transaction data into graph data, wherein the nodes of the graph data are transaction objects contained in the
transaction data, and the edges of the nodes are transaction relationships contained in the
transaction data; determining an initial
community containing a target node based on the graph data; determining a core node set in the initial
community and an attribute initial weight of the core node set; determining a quality index of the initial
community, the quality index including a community density and a community attribute entropy, the community density being used to represent a dense degree of node pairs in the initial community, and the community attribute entropy being used to represent a
confusion degree of nodes in the initial community; expanding the core node set of the initial
community based on the attribute initial weight, the community density and the community attribute entropy to obtain a
local community; and identifying transaction objects corresponding to core nodes included in the
local community as target objects. The present disclosure also provides an object
identification device, equipment, storage medium and program product.