Entailment is an important problem in computational logic particularly relevant to the Inductive Logic Programming (ILP) community as it is at the core of the hypothesis coverage test which is often the bottleneck of an ILP system. Despite developments in resolution heuristics and, more recently, in subsumption engines, most ILP systems simply use Prolog’s left-to-right, depth-first search sele...

This paper addresses the problem of data mining in Inductive Logic Programming (ILP) motivated by its application in the domain of economics. ILP systems have been largely applied to data mining classification tasks with a considerable success. The use of ILP systems in regression tasks has been far less successful. Current systems have very limited numerical reasoning capabilities, which limit...

Inhibitor of apoptosis protein-like protein-2 (ILP-2) has only been detected in the testis and in lymphoblastoid cells. Although previous studies have not reported the presence of ILP-2 in breast cancer tissues, this study indicates the presence of ILP-2 in breast cancer serum samples. To validate whether ILP-2 is a novel serological biomarker for breast cancer, we conducted two-dimensional gel...

We consider a decision-making problem to evaluate absolute ratings of alternatives from the results their pairwise comparisons according two criteria, subject constraints on ratings. formulate as bi-objective optimization constrained matrix approximation in Chebyshev sense logarithmic scale. The is approximate comparison matrices for each criterion simultaneously by common consistent unit rank,...

Collaborative mobile crowdsourcing (CMCS) allows entities, e.g., local authorities or individuals, to hire a team of workers from the crowd connected people, execute complex tasks. In this article, we investigate two different CMCS recruitment strategies allowing task requesters form teams socially and skilled workers: 1) platform-based strategy where platform exploits its own knowledge about 2...

• Complementary advantages • logic can represent domain knowledge in a natural and expressive way • inductive logic programming (ILP) can generate theories and explanations • probabilities allow us to deal with uncertainty and noise in the data • Fixed unknown density ρ on X × Y • The optimal decision would be ρ(Y = 1|x) > 0.5 • Generative direction: model the class conditional densities p(x|y)...

It is challenging to obtain online solutions of large-scale integer linear programming (ILP) problems that occur frequently in slightly different forms during planning for autonomous systems. We refer to such ILP problems as repeated ILP problems. The branch-and-bound (BAB) algorithm is commonly used to solve ILP problems, and a significant amount of computation time is expended in solving nume...

Carin-ALN as proposed recently by Rouveirol and Ventos [2000] is an interesting new rule learning bias for ILP. By allowing description logic terms as predicates of literals in datalog rules, it extends the normal bias used in ILP as it allows the use of all quantified variables in the body of a clause, instead of the normal exist quantified variables and it has atleast and atmost restrictions ...

Discovery of frequent patterns has been studied in a variety of data mining (DM) settings. In its simplest form, known from association rule mining, the task is to nd all frequent itemsets, i.e., to list all combinations of items that are found in a suucient number of examples. A similar task in spirit, but at the opposite end of the complexity scale, is the Inductive Logic Programming (ILP) ap...