Abstract
This paper presents a new approach to build recommendation systems. Multistrategy Inference and Learning System based on the Logic of Plausible Reasoning (LPR) is proposed. Two groups of knowledge transmutations are defined: inference transmutations that are formalized as LPR proof rules, and complex ones that can use machine learning algorithms to generate intrinsically new knowledge. All operators are used by inference engine in a similar manner. In this paper necessary formalism and system architecture are described. Preliminary experimental results of application of the system conclude the work.
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Śnieżyński, B. (2005). Recommendation System Using Multistrategy Inference and Learning. In: Szczepaniak, P.S., Kacprzyk, J., Niewiadomski, A. (eds) Advances in Web Intelligence. AWIC 2005. Lecture Notes in Computer Science(), vol 3528. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11495772_65
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DOI: https://doi.org/10.1007/11495772_65
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-26219-0
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