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2017 | OriginalPaper | Chapter

Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering

Authors : Aleksandra Karpus, Iacopo Vagliano, Krzysztof Goczyła

Published in: Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation

Publisher: Springer International Publishing

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Abstract

Context-aware Recommender Systems aim to provide users with better recommendations for their current situation. Although evaluations of recommender systems often focus on accuracy, it is not the only important aspect. Often recommendations are overspecialized, i.e. all of the same kind. To deal with this problem, other properties can be considered, such as serendipity. In this paper, we study how an ontology-based and context-aware pre-filtering technique which can be combined with existing recommendation algorithm performs in ranking tasks. We also investigate the impact of our method on the serendipity of the recommendations. We evaluated our approach through an offline study which showed that when used with well-known recommendation algorithms it can improve the accuracy and serendipity.

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previous chapter Sorting Data on Ultra-Large Scale with RADULS

next chapter Extending Expressiveness of Knowledge Description with Contextual Approach

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Title: Serendipitous Recommendations Through Ontology-Based Contextual Pre-filtering
Authors: Aleksandra Karpus
Iacopo Vagliano
Krzysztof Goczyła
Publisher: Springer International Publishing
Book: Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation
Print ISBN: 978-3-319-58273-3

Electronic ISBN: 978-3-319-58274-0

Copyright Year: 2017
DOI: https://doi.org/10.1007/978-3-319-58274-0_21

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