2. The system of claim 1 wherein the program is further configured to, prior to the identifying by the ranking module: i. receive, by a template module, from a content database a corpus comprising a set of pre-segmented texts; ii. create, by the template module, a plurality of modified pre-segmented texts for the set of pre-segmented texts by: 1. extraction, by the template module, of a set of semantic terms for each pre-segmented text within the set of pre-segmented texts; and 2. application, by the template module, of at least one domain tag for each pre-segmented text within the set of pre-segmented texts; iii. cluster, by the template module, the plurality of modified pre-segmented texts into one or more conceptual units, wherein each of the one or more conceptual units is associated with one or more templates, wherein each of the one or more templates corresponds to one of the set of pre-segmented texts, and wherein a conceptual unit identifier is assigned to each modified pre-segmented text and pre-segmented text in the plurality of modified pre-segmented texts and set of pre-segmented texts respectively; and iv. store the plurality of modified pre-segmented texts and the set of semantic terms in the content database.
2. The system of claim 1 wherein the program is further configured to, prior to the identifying by the ranking module: i. receive, by a template module, from a content database a corpus comprising a set of pre-segmented texts; ii. create, by the template module, a plurality of modified pre-segmented texts for the set of pre-segmented texts by: 1. extraction, by the template module, of a set of semantic terms for each pre-segmented text within the set of pre-segmented texts; and 2. application, by the template module, of at least one domain tag for each pre-segmented text within the set of pre-segmented texts; iii. cluster, by the template module, the plurality of modified pre-segmented texts into one or more conceptual units, wherein each of the one or more conceptual units is associated with one or more templates, wherein each of the one or more templates corresponds to one of the set of pre-segmented texts, and wherein a conceptual unit identifier is assigned to each modified pre-segmented text and pre-segmented text in the plurality of modified pre-segmented texts and set of pre-segmented texts respectively; and iv. store the plurality of modified pre-segmented texts and the set of semantic terms in the content database. 3. The system of claim 2 wherein the statistical ranking model is adapted to select a sequence of templates that best fit input data, the statistical ranking model being learned by application of historical corpus data for a given domain including conceptual-unit creation and collecting statistics.