We have proposed an extension to the deenition of general integer linear programs (ILP) to accept dis-equality constraints explicitly. A new class of logical variables is introduced to transform the extended ILP in general form to standard form. Branch and Bound algorithm is modiied to solve this new class of ILP.

This book is a collective endeavor of exploring the role of technology in interlanguage pragmatics (ILP) research, instruction, and assessment. It starts with an introduction (Chapter 1) and ends with a commentary and a prologue, both of which envision future directions of using technology in the field of ILP. The included studies are divided into two parts: Part I (Chapters 2 to 6) which addre...

Abstract Inductive logic programming (ILP) is a form of logic-based machine learning. The goal to induce hypothesis (a program) that generalises given training examples and background knowledge. As ILP turns 30, we review the last decade research. We focus on (i) new meta-level search methods, (ii) techniques for learning recursive programs, (iii) approaches predicate invention, (iv) use differ...

Since its introduction in the late 1950s, isolated limb perfusion (ILP) has been the preferred treatment option for locally advanced melanoma and sarcoma confined to a limb. This treatment results in high response rates with a satisfying duration of response in both tumor types. A drawback of ILP, however, is the invasive and complex character of the procedure. Isolated limb infusion (ILI) has ...

This chapter aims at demonstrating that inductive logic programming (ILP), a recently established subfield of machine learning that induces first-order clausal theories from examples, combines very well with the area of deductive databases. In the context of deductive databases, induction can be defined as inference of intensional knowledge from extensional knowledge. Classification-oriented IL...