Abstract: This application discloses a text mining method based on artificial intelligence performed by a computer device. This application includes: obtaining domain candidate term features corresponding to domain candidate terms; obtaining term quality scores corresponding to the domain candidate terms according to the domain candidate term features; determining a new term from the domain candidate terms according to the term quality scores corresponding to the domain candidate terms; obtaining an associated text according to the new term; and determining a domain seed term as a domain new term in response to determining according to the associated text that the domain seed term satisfies a domain new term mining condition. By this application, new terms can be automatically selected from domain candidate terms based on a machine learning algorithm, thereby reducing manpower costs and well adapting to the rapid emergence of special new terms in the Internet era.

Abstract: A method for detecting node types in a directed network is provided. In the method, flow direction feature information of data traffic between network nodes in the directed network is acquired. The flow direction feature information includes a directed graph of nodes representing the network nodes. Layer scores of the nodes in the directed graph are determined based on whether the directed graph includes a directed cycle. The node types of the network nodes represented by the nodes in the directed network are determined according to the layer scores of the nodes.

Abstract: A method for data identification includes determining a target user set from a plurality of users, the target user set comprising at least two users having a first social relationship, wherein a first closeness of the first social relationship among the at least two users in the target user set is higher than a second closeness of a second social relationship between users in the target user set and a user not in the target user set, acquiring a default abnormal user and determining abnormal users in the target user set based on the default abnormal user, determining the status of the target user set based on the abnormal users, and identifying a diffusion-abnormal user from to-be-confirmed users based on social relationships between abnormal users and the to-be-confirmed users in the target user set based on the status of the target user set being abnormal.