1. A method for segmenting a string comprising one or more segments into discrete segments, wherein each of the one or more segments comprises data that is the same as or similar to a marker string, the method comprising: generating a similarity vector comprising a plurality of similarity values and associated locations within the string wherein a similarity value represents a comparison of the marker string and at least a portion of the string and an associated location associated with the similarity value is the location within the string of the start of the at least a portion of the string used in the comparison; identifying a set of ideal segmentation locations based upon an expected number of discrete segments within the string; using the similarity vector to identify a set of candidate segmentation locations; responsive to a candidate segmentation location having a similarity value less than another candidate segmentation location within a local window, removing the candidate segmentation location from the set of candidate segmentation locations; responsive to a candidate segmentation location and a closest ideal segmentation location being at a distance that is greater than the distance threshold, removing the candidate segmentation location from the set of candidate segmentation locations; and using the set of candidate segmentation locations and the set of ideal segmentation locations to generate a set of segmentation locations; and using the set of segmentation locations to segment the string.
1. A method for segmenting a string comprising one or more segments into discrete segments, wherein each of the one or more segments comprises data that is the same as or similar to a marker string, the method comprising: generating a similarity vector comprising a plurality of similarity values and associated locations within the string wherein a similarity value represents a comparison of the marker string and at least a portion of the string and an associated location associated with the similarity value is the location within the string of the start of the at least a portion of the string used in the comparison; identifying a set of ideal segmentation locations based upon an expected number of discrete segments within the string; using the similarity vector to identify a set of candidate segmentation locations; responsive to a candidate segmentation location having a similarity value less than another candidate segmentation location within a local window, removing the candidate segmentation location from the set of candidate segmentation locations; responsive to a candidate segmentation location and a closest ideal segmentation location being at a distance that is greater than the distance threshold, removing the candidate segmentation location from the set of candidate segmentation locations; and using the set of candidate segmentation locations and the set of ideal segmentation locations to generate a set of segmentation locations; and using the set of segmentation locations to segment the string. 4. The method of claim 1 wherein the local window is equal to the number of characters of the marker string.