Languages for Mining and Learning

Applying machine learning and data mining to novel applications is cumbersome. This observation is the prime motivation for the interest in languages for learning and mining. In this talk, I shall provide a gentle introduction to three types of languages that support machine learning and data mining: inductive query languages, which extend database query languages with primitives for mining and learning, modelling languages, which allow to declaratively specify and solve mining and learning problems, and programming languages, that support the learning of functions and subroutines. I shall uses an example of each type of language (the mining views for inductive querying, MiningZinc for modelling and ProbLog for probabilistic programming) to introduce the underlying ideas and to put them into a common perspective. This then forms the basis for a short analysis of the state-of-the-artstatus: publishe