In some example embodiments, a system and method are provided for graph pattern analysis. In example embodiments, pattern data of a primary network that includes data relating to relationships between entities are received. A reference matrix comprising a plurality of secondary network determined based on the pattern data of the primary network is generated A graphical display of the primary network and the reference matrix are displayed on a user interface. A selection of a secondary network from the plurality of secondary networks of the reference matrix is received. The selected secondary network has similar matching characteristics with at least a portion of the primary network. In response to the selection, the primary network is classified as a classification type related to the selected secondary network.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method comprising: receiving pattern data of a primary network that includes data relating to relationships between entities; generating, using a processor of a machine, a reference matrix comprising a plurality of secondary networks determined based on the pattern data of the primary network; causing graphical display of the primary network and the reference matrix on a user interface; receiving a selection of a secondary network from the plurality of secondary networks of the reference matrix, the selected secondary network having similar matching characteristics with at least a portion of the primary network; and classifying the primary network as a classification type related to the selected secondary network. 2. The method of claim 1, further comprising storing the primary network for future use as a secondary network having the classification type. 3. The method of claim 1, further comprising generating the plurality of secondary networks using an algorithm that processes pattern characteristics extracted from the pattern data. 4. The method of claim 3, wherein the generating the plurality of secondary network comprises parsing the pattern data using a retrieved parsing grammar to determine the pattern characteristics. 5. The method of claim 3, further comprising generating a pattern characteristic set based on the extracted pattern characteristics. 6. The method of claim 5, wherein the generating the plurality of secondary networks comprises combining selected historical data and the pattern characteristic set based on a crossover function. 7. The method of claim 5, wherein the generating the plurality of secondary networks comprises combining selected historical data and the pattern characteristic set based on a mutation function. 8. The method of claim 1, further comprising generating the plurality of secondary networks, the generating the plurality of secondary networks comprising: mapping the pattern data to patterns stored in a database; and retrieving the stored patterns that map to the pattern data; the retrieved stored patterns being the plurality of secondary networks. 9. The method of claim 1, further comprising causing display of a popup that contains a description of one of the plurality of secondary networks in response to a pointer selection of the one of the plurality of secondary networks. 10. A system comprising: one or more processors of a machine configured to at least: receive pattern data of a primary network that includes data relating to relationships between entities; generate a reference matrix comprising a plurality of secondary networks determined based on the pattern data of the primary network; cause graphical display of the primary network and the reference matrix on a user interface; receive a selection of a secondary network from the plurality of secondary networks of the reference matrix, the selected secondary network having similar matching characteristics with at least a portion of the primary network; and classify the primary network as a classification type related to the selected secondary network. 11. The system of claim 10, wherein the one or more processors are further configured to store the primary network for future use as a secondary network having the classification type. 12. The system of claim 10, wherein the one or more processors are further configured to generate the plurality of secondary networks of the reference network using an algorithm that processes pattern characteristics extracted from the pattern data. 13. The system of claim 10, wherein the one or more processors are further configured to generate the plurality of secondary networks by performing operations comprising: mapping the pattern data to patterns stored in a database; and retrieving the stored patterns that map to the pattern data; the retrieved stored patterns being the plurality of secondary networks. 14. A machine-readable medium having no transitory signals and comprising instructions which, when implemented by one or more processors of a machine, cause the machine to perform operations comprising: receiving pattern data of a primary network that includes data relating to relationships between entities; generating a reference matrix comprising a plurality of secondary networks determined based on the pattern data of the primary network; causing graphical display of the primary network and the reference matrix on a user interface; receiving a selection of a secondary network from the plurality of secondary networks of the reference matrix, the selected secondary network having similar matching characteristics with at least a portion of the primary network; and classifying the primary network as a classification type related to the selected secondary network. 15. The machine-readable medium of claim 14, wherein the operations further comprise storing the primary network for future use as a secondary network having the classification type. 16. The machine-readable medium of claim 14, wherein the operations further comprise generating the plurality of secondary networks using an algorithm that processes pattern characteristics extracted from the pattern data. 17. The machine-readable medium of claim 16, wherein the operations further comprise generating a pattern characteristic set based on the extracted pattern characteristics. 18. The machine-readable medium of claim 17, wherein the generating the plurality of secondary networks comprises combining selected historical data and the pattern characteristic set based on a crossover function. 19. The machine-readable medium of claim 17, wherein the generating the plurality of secondary networks comprises combining selected historical data and the pattern characteristic set based on a mutation function. 20. The method of claim 1, wherein the operations further comprise generating the plurality of secondary networks, the generating the plurality of secondary networks comprising: mapping the pattern data to patterns stored in a database; and retrieving the stored patterns that map to the pattern data; the retrieved stored patterns being the plurality of secondary networks.