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On How Networks Stabilize User Interest Based Methods and Vice Versa

Authors:
László Grad-Gyenge
Peter Filzmoser

Keywords: recommender system; graph based; knowledge graph; explicit feedback; receiver operating characteristic

Abstract:
This paper presents the evaluation of two graph-based recommendation methods compared to collaborative filtering as the baseline. The evaluation is primarily based on the investigation of the Average Receiver operating Characteristic curve on the MovieLens dataset. The presented methods operate on the knowledge graph, which information representation technique is also discussed in this paper. The evaluation results show that combining a network based and a user interest based method leads to a more stable performance and an increase in the recommendation quality.

Pages: 33 to 40

Copyright: Copyright (c) IARIA, 2017

Publication date: March 19, 2017

Published in: conference

ISSN: 2308-4375

ISBN: 978-1-61208-542-5

Location: Nice, France

Dates: from March 19, 2017 to March 23, 2017