Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
CSLP'04 Proceedings of the First international conference on Constraint Solving and Language Processing
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Integer linear programming (ILP) is a framework for solving combinatorial problems with linear constraints of the form y = c1x1 + c2x2 + … + cnxn where the variables (ie., y and xis) take on only integer values. ILP is a special case of a larger family of contraint-based solving techniques in which variables may take on additional types of values (eg. discrete, symbolic, real, set, and structured) or involve additional kinds of constraints (eg. logical and non-linear, such as x Λ y ⇒ z and y = cxn). Constraint based problem solving approaches offer a more natural way of modeling many kinds of realworld problems. Furthermore, the declarative nature of constraint-based approaches makes them versatile since the order in which the variables are solved is not predetermined. The same program can thus be reused for solving different subsets of the problem's variables. Additionally, in some cases, constraintbased approaches can solve problems more efficiently or accurately than alternative approaches.