A method and system are disclosed for solving an optimization problem involving graph similarity in more than one graph using a binary optimizer, the method comprising obtaining, in a digital computer, an optimization problem involving graph similarity; generating, using the digital computer, at least one binary optimization problem representative of the optimization problem; providing the generated at least one binary optimization problem to a binary optimizer in an analog computer; the digital computer obtaining from a binary optimizer binary solutions generated by solving the at least one binary optimization problem using the binary optimizer; and the digital computer providing an indication of a maximum common subgraph in the more than one graph using the generated binary solutions.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A method for solving an optimization problem involving graph similarity in more than one graph using a binary optimizer, the method comprising: obtaining, in a digital computer, an optimization problem involving graph similarity; generating, using the digital computer, at least one binary optimization problem representative of the optimization problem; providing the generated at least one binary optimization problem to a binary optimizer in an analog computer; solving the at least one binary optimization problem using the binary optimizer to generate binary solutions; the digital computer receiving the generated binary solutions from the binary optimizer; and the digital computer providing an indication of a maximum common subgraph in the more than one graph using the generated binary solutions. 2. The method as claimed in claim 1, wherein the optimization problem involves graph similarity in a plurality of graphs, further comprising iteratively executing in the digital computer a classifier with the indication of a maximum common subgraph of at least one pair of graphs to determine a best classifier and the digital computer providing an indication of the best classifier. 3. The method as claimed in claim 1, wherein the at least one optimization problem is obtained from at least one of a user, a computer, a software package and an agent. 4. The method as claimed in claim 2, wherein the indication of the best classification is provided by the digital computer to at least one of a user, a memory of said digital computer and another computer operatively connected to the digital computer. 5. A method for solving an optimization problem involving graph similarity in more than one graph using a binary optimizer, the method comprising: obtaining, in a digital computer, an optimization problem involving graph similarity; generating, using the digital computer, at least one binary optimization problem representative of the optimization problem; providing the generated at least one binary optimization problem to a binary optimizer in an analog computer; the digital computer obtaining from a binary optimizer binary solutions generated by solving the at least one binary optimization problem using the binary optimizer; and the digital computer providing an indication of a maximum common subgraph in the more than one graph using the generated binary solutions. 6. The method as claimed in claim 5, wherein the optimization problem involves graph similarity in two graphs, further comprising executing in the digital computer a classifier with the indication of a maximum common subgraph to determine a best classification and the digital computer providing an indication of the best classification. 7. The method as claimed in claim 1, wherein the at least one binary optimization problem comprises at least one polynomial in binary variables. 8. A digital computer comprising: a central processing unit; a display device; a communication port for connecting the digital computer to a binary optimizer in an analog computer; a memory unit comprising an application for solving an optimization problem involving graph similarity in more than one graph, the application comprising: instructions for obtaining, in the digital computer, an optimization problem involving graph similarity; instructions for generating, using the digital computer, at least one binary optimization problem representative of the optimization problem; instructions for providing the generated at least one binary optimization problem to a binary optimizer in an analog computer; instructions for obtaining, via the communication port, binary solutions generated by solving the at least one binary optimization problem using the binary optimizer; and instructions for providing an indication of a maximum common subgraph in the more than one graph using the generated binary solutions. 9. The digital computer as claimed in claim 8, wherein the optimization problem involves graph similarity in a plurality of graphs, further wherein the application further comprises instructions for iteratively executing a classifier with the indication of a maximum common subgraph of at least one pair of graphs to determine a best classifier and instructions for providing an indication of the best classifier. 10. A non-transitory computer-readable storage medium for storing computer- executable instructions which, when executed, cause a digital computer to perform a method for solving an optimization problem involving graph similarity in more than one graph using a binary optimizer, the method comprising obtaining, in the digital computer, an optimization problem involving graph similarity; generating, using the digital computer, at least one binary optimization problem representative of the optimization problem; providing the generated at least one binary optimization problem to a binary optimizer in an analog computer; the digital computer obtaining from a binary optimizer binary solutions generated by solving the at least one binary optimization problem using the binary optimizer; and the digital computer providing an indication of a maximum common subgraph in the more than one graph using the generated binary solutions.