Valued constraint satisfaction problems with ordered variables (VCSPO) are a special case of Valued CSPs in which variables are totally ordered and soft constraints are imposed on tuples of variables that do not violate the order. We study a restriction of VCSPO, in which soft constraints are imposed on a segment of adjacent variables and a constraint language consists of -valued characteristic functions of predicates. This kind of potentials generalizes the so-called pattern-based potentials, which were applied in many tasks of structured prediction. For a constraint language we introduce a closure operator, , and give examples of constraint languages for which is small. If all predicates in are cartesian products, we show that the minimization of a generalized pattern-based potential (or, the computation of its partition function) can be made in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\varvec{\mathcal O}}(|\varvec{V}|\cdot |\varvec{D}|\varvec{^2} \cdot |\overline{\varvec{\Gamma }^{\cap }}|\varvec{^2})$$\end{document} time, where \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{V}$$\end{document} is a set of variables, \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\varvec{D}$$\end{document} is a domain set. If, additionally, only non-positive weights of constraints are allowed, the complexity of the minimization task drops to \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\varvec{\mathcal O}}(|\varvec{V}|\cdot |\overline{\varvec{\Gamma }^{\cap }}| \cdot |\varvec{D}| \cdot \varvec{\max }_{\varrho \in \varvec{\Gamma }}\Vert \varrho \Vert \varvec{^2})$$\end{document} where is the arity of . For a general language and non-positive weights, the minimization task can be carried out in \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$${\varvec{\mathcal O}}(|\varvec{V}|\cdot |\overline{\varvec{\Gamma }^{\cap }}|\varvec{^2})$$\end{document} time. We argue that in many natural cases is of moderate size, though in the worst case can blow up and depend exponentially on .