Abstract: There is provided a computer-implemented method for processing a plurality of data inputs comprising information about a network. A plurality of machine learning models is trained (102) on the plurality of data inputs. Each machine learning model of the plurality of machine learning models is trained to generate a representation of at least one data input of the plurality of data inputs. A representation of each data input of the plurality of data inputs is generated (104) using at least one trained machine learning model of the plurality of trained machine learning models. The plurality of trained machine learning models and the generated representation of each data input are for use in resolving an issue in the network.

Abstract: There is provided a computer-implemented method for analysing one or more network attributes of a network. One or more first network attributes of the network are analysed using a first machine learning model to generate a first output comprising information about an event in the network. If an estimated confidence level for the first output is less than a confidence level threshold, the one or more first network attributes are analysed using a second machine learning model to generate a second output. The second output is indicative of one or more second network attributes of the network to analyse using the first machine learning model.

Abstract: There is provided a computer-implemented method for processing a plurality of data inputs comprising information about a network. A plurality of machine learning models is trained (102) on the plurality of data inputs. Each machine learning model of the plurality of machine learning models is trained to generate a representation of at least one data input of the plurality of data inputs. A representation of each data input of the plurality of data inputs is generated (104) using at least one trained machine learning model of the plurality of trained machine learning models. The plurality of trained machine learning models and the generated representation of each data input are for use in resolving an issue in the network.

Abstract: There is provided a computer-implemented method for analysing one or more network attributes of a network. One or more first network attributes of the network are analysed using a first machine learning model to generate a first output comprising information about an event in the network. If an estimated confidence level for the first output is less than a confidence level threshold, the one or more first network attributes are analysed using a second machine learning model to generate a second output. The second output is indicative of one or more second network attributes of the network to analyse using the first machine learning model.