Probabilistic Inductive Logic Programming

Probabilistic Inductive Logic Programming
Springer; 1 edition | June 2, 2010 | ISBN-10: 3540786511 | 349 pages | File type: PDF | 4.82 mb

The question, how to combine probability and logic with learning, is getting an increased attention in several disciplines such as knowledge representation, reasoning about uncertainty, data mining, and machine learning simulateously. This results in the newly emerging subfield known under the names of statistical relational learning and probabilistic inductive logic programming.
This book provides an introduction to the field with an emphasis on the methods based on logic programming principles. It is concerned with formalisms and systems, implementations and applications, as well as with the theory of probabilistic inductive logic programming.

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