A method/system may construct an expectation tree based upon an input flow, the expectation tree having a root node, nodes, each path from a root node to a node representing a potential input sequence from the input flow, each node including a counter for a number of occurrences of the respective potential input sequence. The method/system may construct touch distribution functions representing a weighted sum of prior touch prints for the targets, determine expectation weights of the potential input sequences and based upon expectations of pairs of sequences in the expectation tree, determine touch weights of potential input sequences toward a sequence of input touch prints and based upon the touch distribution functions, build an ordered list of input candidate sequences, and display the ordered list to the user for selection and confirmation of a desired input candidate sequence.
Please help me write a proper abstract based on the patent claims. CLAIM: 1. A system of input sequence prediction and recognition, the system comprising: an input component configured to register touch prints representing an input interaction between input surface and input object for selection of input values, associated with a plurality of input targets; and a processor coupled to said input component and configured to construct an expectation tree based upon an input flow, the expectation tree comprising a root node, a plurality of nodes, wherein each path from a root node to a node represents a potential input sequence from the input flow, and wherein each node comprises a counter for a number of occurrences of said respective potential input sequence, construct touch distribution functions representing a weighted sum of prior touch prints for the plurality of targets, determine expectation weights of the potential input sequences and based upon expectations of pairs of sequences in the expectation tree, determine touch weights of potential input sequences toward a sequence of input touch prints and based upon the touch distribution functions, build an ordered list of input candidate sequences, the order being based upon their combined weight, wherein combined weight is a product of expectation and touch weights, and display the ordered list to the user for selection and confirmation of a desired input candidate sequence. 2. The system of claim 1 wherein the input interaction comprises a plurality of touch taps of input targets at the input surface, corresponding to the input sequence. 3. The system of claim 1 wherein the input interaction comprises a continuous input trace connecting input targets at the input surface, corresponding to the input sequence. 4. The system of claim 3 wherein said processor is configured to recognize partial traces between consecutive targets for input target recognition. 5. The system of claim 3 wherein said processor is configured to recognize positions of sharp directional turns of the continuous input trace at the input surface as positions of touch input interaction. 6. The system of claim 1 wherein said processor is configured to add accepted input candidate sequences from the input flow to the expectation tree by adding a new leaf node and respective path to the expectation tree. 7. The system of claim 6 wherein said processor is configured to add consecutive, non-overlapping accepted candidate sequences from the input flow to the expectation tree. 8. The system of claim 6 wherein said processor is configured to add accepted candidate sequences starting at every input value from the input flow to the expectation tree. 9. The system of claim 1 wherein the expectation weight of a respective potential input sequence is a value measuring a number of potentially saved inputs if a predicted sequence is correct. 10. The system of claim 9 wherein the expectation Weight of the respective potential input sequence is a product of maximal expectation of the respective potential input sequence after all possible previous sequences in a current input flow and a length of the respective potential input sequence. 11. The system of claim 1 wherein the touch weight of the respective potential input sequence comprises a value measuring a spatial proximity of an input trace and expected input trace for the respective potential input sequence. 12. The system of claim 11 wherein the touch weight of the respective potential input sequence is a product of touch weights of input targets corresponding to inputs of said input sequence; and wherein the touch weight of a target is an integral of the product of touch print and target distribution function. 13. The system of claim 1 wherein the input candidate sequences are word aligned and comprise at least one word. 14. The system of claim 1 wherein the input candidate sequences comprise sequences of input values of an arbitrary length. 15. The system of claim 1 wherein the input candidate sequences are limited to one letter; wherein the plurality of input targets has a common centered distribution function; and wherein input precognition is determined by cells of a functional Voronoi diagram for target distribution functions, weighted by expectation weights of inputs, assigned to the plurality of input targets. 16. The system of claim 1 wherein a default candidate sequence comprising a candidate sequence with a greatest combined weight, is displayed in an input field of an application; and wherein the user confirms input of any part of the default candidate sequence. 17. The system of claim 1 wherein said processor is configured to detect and correct misprinted candidate sequences upon user request. 18. The system of claim 1 wherein said processor is configured to expand a predicted sequence inductively, using a predicted sequence for prediction of a new sequence at a subsequent stage. 19. The system of claim 1 wherein said processor is configured to use the expectation tree for data compression with prediction of the input flow for storing of input history between sessions and transmission to another system. 20. The system of claim 1 wherein the plurality of input targets comprises regions of arbitrary shape at the input surface. 21. The system of claim 1 wherein the plurality of input targets comprises keys of a keyboard. 22. The system of claim 1 wherein the plurality of input targets comprises objects of a 2-dimensional input interface. 23. The system of claim 1 wherein the plurality of input targets comprises objects of 1-dimensional input interface. 24. A method of input sequence prediction and recognition comprising: operating an input component to register touch prints representing an input interaction between input surface and input object for selection of input values, associated with a plurality of input targets; and operating a processor coupled to the input component and to construct an expectation tree based upon an input flow, the expectation tree comprising a root node, a plurality of nodes, wherein each path from a root node to a node represents a potential input sequence from the input flow, and wherein each node comprises a counter for a number of occurrences of the respective potential input sequence, construct touch distribution functions representing a weighted sum of prior touch prints for the plurality of targets, determine expectation weights of the potential input sequences and based upon expectations of pairs of sequences in the expectation tree, determine touch weights of potential input sequences toward a sequence of input touch prints and based upon the touch distribution functions, build an ordered list of input candidate sequences, the order being based upon their combined weight, wherein combined weight is a product of expectation and touch weights, and display the ordered list to the user for selection and confirmation of a desired input candidate sequence. 25. The method of claim 24 wherein the input interaction comprises a plurality of touch taps of input targets at the input surface, corresponding to the input sequence. 26. The method of claim 24 wherein the input interaction comprises a continuous input trace connecting input targets at the input surface, corresponding to the input sequence. 27. The method of claim 26 further comprising operating the processor to recognize positions of sharp directional turns of the continuous input trace at the input surface as positions of touch input interaction. 28. The method of claim 24 further comprising operating the processor to add accepted input candidate sequences from the input flow to the expectation tree by adding a new leaf node and respective path to the expectation tree. 29. The method of claim 24 wherein the expectation weight of a respective potential input sequence is a value measuring a number of potentially saved inputs if a predicted sequence is correct. 30. The method of claim 24 wherein the touch weight of the respective potential input sequence comprises a value measuring a spatial proximity of an input trace and expected input trace for the respective potential input sequence. 31. The method of claim 24 wherein the input candidate sequences comprise sequences of input values of an arbitrary length. 32. The method of claim 24 wherein a default candidate sequence comprising a candidate sequence with a greatest combined weight, is displayed in an input field of an application; and wherein the user confirms input of any part of the default candidate sequence. 33. The method of claim 24 wherein the plurality input targets comprises keys of a keyboard.