A Knowledge-based Recommendation Framework using SVN Numbers

Abstract

Current knowledge based recommender systems, despite
proven useful and having a high impact, persist with some
shortcomings. Among its limitations are the lack of more
flexible models and the inclusion of indeterminacy of the
factors involved for computing a global similarity. In this
paper, a new knowledge based recommendation models
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based SVN number is presented. It includes database
construction, client profiling, products filtering and
generation of recommendation. Its implementation makes
possible to improve reliability and include indeterminacy
in product and user profile. An illustrative example is
shown to demonstrate the model applicability.