Mining of composite patterns across multiple multidimensional data sources

A device for identifying patterns in data streams, said device comprising:

• processing circuitry configured to
• receive a plurality of data streams segmented in the same time range from one or more input data sources;
• identify at least one simple pattern in at least one data stream of the plurality of data streams provided by different data sources, each data stream in the data streams including a linear sequence of data objects, the simple pattern including repetition of a data object of the data objects,
• identify at least one multi-pattern in at least one data stream of the plurality of data streams, the multi-pattern including repetition of a data block, the data block including at least two contiguous data objects that are in the same order in the data block,
• identify at least one composite pattern between a first data stream and a second data stream by
• identifying at least one first data object and a first data block in the first data stream and at least one second data object and a second data block in the second data stream that repeat together in the same pattern, and
• analyzing correlations between the first data object and the second data object and the first data block and the second data block based on co-occurrences at the same position within the first and second streams, respectively,
• derive new pattern data at the same position within the same time range based on the analyzing, and
• identify and outputting anomalies by mining the new pattern data, wherein all patterns are accessed simultaneously.

A non-transitory computer-readable medium having computer-readable instructions stored thereon which when executed by a computer cause the computer to perform a method for identifying patterns in data streams, the method comprising:

• receiving a plurality of data streams segmented in the same time range from one or more input data sources;
• identifying at least one simple pattern in at least one data stream of the plurality of data streams provided by different data sources, each data stream including a linear sequence of data objects, the simple pattern including repetition of a data object in the linear sequence of data objects;
• identifying at least one multi-pattern in at least one data stream of the plurality of data streams, the multi-pattern including repetition of a data block, the data block including at least two contiguous data objects that are in the same order in the data block;
• identifying at least one composite pattern between a first data stream and a second data stream by
• identifying at least one first data object and a first data block in the first data stream and at least one second data object and a second data block in the second data stream that repeat together in the same pattern, and
• analyzing correlations between the first data object and the second data object and the first data block and the second data block based on co-occurrences at the same position within the first and second streams, respectively;
• deriving new pattern data at the same position within the same time range based on the analyzing;
• and
• identifying and outputting anomalies by mining the new pattern data,
• wherein all patterns are accessed simultaneously.