A combinatorial optimization problem arising from text classification

We study a combinatorial optimization problem related to the automatic classification of texts. The problem consists of covering a given text using strings from a given set, where a cost is incurred for each type of string used. We give a 0-1 linear programming formulation and we report on computational experiences on very large instances using two different Lagrangean relaxations and heuristic algorithms based on simulated annealing and threshold accepting.