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(Partial) user preference similarity as classification-based model similarity


Bouza, Amancio; Bernstein, Abraham (2014). (Partial) user preference similarity as classification-based model similarity. Semantic Web, 5(1):47-64.

Abstract

Recommender systems play an important role in helping people finding items they like. One type of recommender system is collaborative filtering that considers feedback of like-minded people. The fundamental assumption of collaborative filtering is that people who previously shared similar preferences behave similarly later on. This paper introduces several novel, classification-based similarity metrics that are used to compare user preferences. Furthermore, the concept of partial preference similarity based on a machine learning model is presented. For evaluation the cold-start behavior of the presented classification-based similarity metrics is evaluated in a large-scale experiment. It is shown that classification-based similarity metrics with machine learning significantly outperforms other similarity approaches in different cold-start situations under different degrees of data-sparseness.

Abstract

Recommender systems play an important role in helping people finding items they like. One type of recommender system is collaborative filtering that considers feedback of like-minded people. The fundamental assumption of collaborative filtering is that people who previously shared similar preferences behave similarly later on. This paper introduces several novel, classification-based similarity metrics that are used to compare user preferences. Furthermore, the concept of partial preference similarity based on a machine learning model is presented. For evaluation the cold-start behavior of the presented classification-based similarity metrics is evaluated in a large-scale experiment. It is shown that classification-based similarity metrics with machine learning significantly outperforms other similarity approaches in different cold-start situations under different degrees of data-sparseness.

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3 citations in Web of Science®
4 citations in Scopus®
3 citations in Microsoft Academic
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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:03 Faculty of Economics > Department of Informatics
Dewey Decimal Classification:000 Computer science, knowledge & systems
Language:English
Date:2014
Deposited On:14 Mar 2013 15:26
Last Modified:29 Nov 2018 17:42
Publisher:IOS Press
ISSN:1570-0844
OA Status:Green
Free access at:Related URL. An embargo period may apply.
Publisher DOI:https://doi.org/10.3233/SW-130099
Official URL:http://www.semantic-web-journal.net/content/partial-user-preference-similarity-classification-based-model-similarity
Other Identification Number:merlin-id:7938

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