A conceptual clustering is a set of formal concepts (i.e., closed itemsets) that defines a partition of a set of transactions. Finding a conceptual clustering is an NP-complete problem for which Constraint Programming (CP) and Integer Linear Programming (ILP) approaches have been recently proposed. We introduce new CP models to solve this problem: a pure CP model that uses set constraints, and ...

In the contemporary customer-driven supply chain, maximization of customer service plays an equally important role as minimization of costs for a company to retain and increase its competitiveness. This article develops a multiple-criteria optimization approach, combining the analytic hierarchy process (AHP) and an integer linear programming (ILP) model, to aid the design of an optimal logistic...

This article presents an overview of existing ILP and non ILP approaches to word morphology learning and sets targets for future research The article claims that new challenges to the ILP community with more appeal to computational linguists should be sought in a whole new range of unexplored learning tasks in which ILP would have to make a more extensive use of relevant linguistic knowledge an...

Many Integer Linear Programming (ILP) problems contain significant subproblems exclusively composed of 0-1 (binary) variables. Much effort has gone in to special solvers for 0-1 ILP, as well as specialized versions of 0-1 ILP. The boolean satisfiability problem (SAT), is fundamental to many fields, including Artificial Intelligence, Formal Verification, and Computer Aided Design, and can be vie...

Ratings are important for building up trust among different parties. Since the arrival of the internet era in the 1990s, countless online rating systems have emerged. For example, Amazon.com established a rating system for books and other products in 1995. Today online rating can be found everywhere, be it e-commerce sites, social networks, and information or recommendation platforms. In most c...

ABSTRACT Background: Osteoid osteoma is a benign bony neoplasm and its classic treatment is surgery. In the r ecent decades percutaneous laser therapy was suggested to be replaced by surgery. In this study we have reviewed the results of the first applications of interstitial laser photocoagulation (ILP) for treatment of osteoid osteoma in Iranian patients. Materials and Methods: In this case s...

The generic task of Inductive Logic Programming (ILP) is to search a predeened subspace of rst-order logic for hypotheses that in some respect explain examples and background knowledge. In this paper we consider the development of parallel implementations of ILP systems. A rst part discusses the division of the ILP-task into subtasks that can be handled concurrently by multiple processes execut...

Inductive Logic Programming (ILP) combines both Machine Learning and Logic Programming techniques. ILP uses rst-order predicate logic restricted to Horn clauses as an underlying language. Thus, programs induced by an ILP system inherit the classical limitations of PROLOG programs. Constraint Logic Programming avoids some of the limitations of Logic Programming and so ILP aims to induce programs...

Inductive Logic Programming (ILP) is a Machine Learning technique that has been quite successful in knowledge discovery for relational domains. ILP systems implemented in Prolog challenge the limits of Prolog systems due to heavy usage of resources such as database accesses and memory usage, and to very long execution times. The major reason to implement ILP systems in Prolog is that the infere...