We provide a new formulation for the problem of learning the optimal classification tree of a
given depth as a binary linear program. A limitation of previously proposed Mathematical …

Data Mining: Concepts and Techniques, Fourth Edition introduces concepts, principles, and
methods for mining patterns, knowledge, and models from various kinds of data for diverse …

This paper proposes a tentative and original survey of meeting points between Knowledge
Representation and Reasoning (KRR) and Machine Learning (ML), two areas which have …

The field of data mining has become accustomed to specifying constraints on patterns of
interest. A large number of systems and techniques has been developed for solving such …

Constrained Clustering allows to make the clustering task more accurate by integrating user
constraints, which can be instance-level or cluster-level constraints. Few works consider the …

One of the biggest challenges in the design of real-world decision support systems is
coming up with a good combinatorial optimization model. Often enough, accurate predictive …

We encode the problem of learning the optimal decision tree of a given depth as an integer
optimization problem. We show experimentally that our method (DTIP) can be used to learn …

Due to the availability of various open source Machine Learning (ML) tools and libraries,
developers nowadays can easily implement their purposes by just invoking machine …

In a sequential auction with multiple bidding agents, the problem of determining the ordering
of the items to sell in order to maximize the expected revenue is highly challenging. The …

Knowledge Graphs (KGs) are becoming the core of most artificial intelligent and cognitive
applications. Popular KGs such as DBpedia and Wikidata have chosen the RDF data model …