1. A computer-implemented optimization method for instance-based sentence boundary determination comprising the steps of: setting by a computer an initial upper bound (UB) of a cost associated with an optimized solution to a lowest cost derived by several greedy algorithms; identifying by the computer all corpus instances stored in an electronic database that contains one or more of a plurality of desired propositions; forming by the computer a search tree structure with branches for each of plurality of identified corpus instances that contain one or more of said plurality of desired propositions; deleting by the computer one or more of a plurality of undesired propositions from said identified corpus instances; updating by the computer an overall cost with one or more deletion costs; inserting by the computer one or more of said plurality of desired propositions that were not contained in said corpus instance into said corpus instance; updating by the computer the overall cost with one or more insertion costs; calculating by the computer a lower bound (LB) of a cost associated with a current solution or partial solution; pruning by the computer a current search branch if the LB is greater than the UB; recursively computing by the computer a best solution associated with generating one or more additional sentences to convey the rest of said plurality of desired propositions that were not contained in said corpus instance; updating by the computer the overall cost with a boundary cost plus a cost associated with the best solution found by the recursively computing procedure; updating by the computer UB if the current overall cost is lower than UB; and outputting by the computer a solution that has the lowest overall cost using a set of said identified corpus instances with a set of said deletion, insertion and sentence break operations.
1. A computer-implemented optimization method for instance-based sentence boundary determination comprising the steps of: setting by a computer an initial upper bound (UB) of a cost associated with an optimized solution to a lowest cost derived by several greedy algorithms; identifying by the computer all corpus instances stored in an electronic database that contains one or more of a plurality of desired propositions; forming by the computer a search tree structure with branches for each of plurality of identified corpus instances that contain one or more of said plurality of desired propositions; deleting by the computer one or more of a plurality of undesired propositions from said identified corpus instances; updating by the computer an overall cost with one or more deletion costs; inserting by the computer one or more of said plurality of desired propositions that were not contained in said corpus instance into said corpus instance; updating by the computer the overall cost with one or more insertion costs; calculating by the computer a lower bound (LB) of a cost associated with a current solution or partial solution; pruning by the computer a current search branch if the LB is greater than the UB; recursively computing by the computer a best solution associated with generating one or more additional sentences to convey the rest of said plurality of desired propositions that were not contained in said corpus instance; updating by the computer the overall cost with a boundary cost plus a cost associated with the best solution found by the recursively computing procedure; updating by the computer UB if the current overall cost is lower than UB; and outputting by the computer a solution that has the lowest overall cost using a set of said identified corpus instances with a set of said deletion, insertion and sentence break operations. 6. The method of claim 1 wherein said step of inserting one or more of a plurality of desired propositions into said identified corpus is performed using an insertion cost of: 
 Cost i ( E )= W i *Σ p j εE i cost(*, p j ) wherein, a set of variables of said set of relationship includes: C 1 is the corpus instance selected, E is a set of propositions to be inserted into C i , icost is an insertion cost, W i is an insertion weight, and p i is a proposition in E.