5. The method according to claim 3 , wherein the generating the topic-network service correspondence according to the topic-network service probability matrix comprises: performing, if one network service belongs to two or more topics in the topic-network service probability matrix, arrangement according to a descending order of probability that the network service belongs to each topic, and keeping first M topics as topics to which the network service belongs, M being a positive integer; and generating the topic-network service correspondence according to the network service and the first M topics to which the network service belongs; or, performing, if one network service belongs to two or more topics in the topic-network service probability matrix, arrangement according to a descending order of probability that the network service belongs to each topic, and keeping topics whose probabilities are greater than a preset threshold as topics to which the network service belongs; and generating the topic-network service correspondence according to the network service and the first M topics to which the network service belongs.
3. The method according to claim 2 , wherein the inputting the label sequence of each network service in a topic generation model, to obtain the label-topic correspondence and the topic-network service correspondence comprises: inputting the label sequence of each network service in a latent Dirichlet allocation (LDA) model, to obtain a label-topic probability matrix and a topic-network service probability matrix, the label-topic probability matrix comprising at least one topic, a label corresponding to each topic, and a probability that each label belongs to a corresponding topic; and the topic-network service probability matrix comprising at least one topic, a network service corresponding to each topic, and a probability that each network service belongs to a corresponding topic; generating the label-topic correspondence according to the label-topic probability matrix; and generating the topic-network service correspondence according to the topic-network service probability matrix.