Abstract: Patterns of change in system operating parameters are identified which may be used to identify unexpected operational conditions and to trigger an appropriate alert or action. A network is controlled using operating data for the network. Network operating data is received and divided into sequential time periods. A structural description such as an association rule is determined for the received data in each time period and a change pattern in the determined structural description is identified over the time periods. The network is then controlled using a predetermined action corresponding to a predetermined structural description change pattern in response to the identified structural description change pattern matching the predetermined structural description change pattern.

Abstract: The present invention provides a method of detecting the growth and development of clusters in a data set. The data set is divided into a number of slices and an algorithm is applied to the data held in each data slice set. Each slice can be compared with the subsequent slice to determine which clusters persist from slice to slice. Random data agglomerations in a single slice may give the appearance of a cluster but their random nature means that they are unlikely to persist so those clusters that persist across a number of slices, or that show the strongest measure of persistence, are most likely to represent a data cluster that represents a situation of interest.

Abstract: The present invention relates to identifying patterns of change in system operating parameters which may be used to identify unexpected operational conditions and to trigger an appropriate alert or action. The present invention provides a method (300) for controlling a network (350) using operating data for the network, the method comprising: receiving the network operating data (110); dividing the received data into sequential time periods (305); determining a structural description such as an association rule for the received data in each time period (310); identifying a change pattern in the determined structural description over the time periods (315); controlling the network (325) using a predetermined action corresponding to a predetermined structural description change pattern in response to the identified structural description change pattern matching the predetermined structural description change pattern (320).

Abstract: The present invention provides a method of detecting the growth and development of clusters in a data set. The data set is divided into a number of slices and an algorithm is applied to the data held in each data slice set. Each slice can be compared with the subsequent slice to determine which clusters persist from slice to slice. Random data agglomerations in a single slice may give the appearance of a cluster but their random nature means that they are unlikely to persist so those clusters that persist across a number of slices, or that show the strongest measure of persistence, are most likely to represent a data cluster that represents a situation of interest.