Using the Context of User Feedback in Recommender Systems

Our work is generally focused on recommending for small or medium-sized e-commerce portals, where explicit feedback is absent and thus the usage of implicit feedback is necessary. Nonetheless, for some implicit feedback features, the presentation context may be of high importance. In this paper, we...

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Bibliographic Details
Main Author: Ladislav Peska
Format: Article
Language:English
Published: Open Publishing Association 2016-12-01
Series:Electronic Proceedings in Theoretical Computer Science
Online Access:http://arxiv.org/pdf/1612.04978v1
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spelling doaj-a648016590de4d0f88de3ff12e823c8b2020-11-24T23:24:04ZengOpen Publishing AssociationElectronic Proceedings in Theoretical Computer Science2075-21802016-12-01233Proc. MEMICS 201611210.4204/EPTCS.233.1:1Using the Context of User Feedback in Recommender SystemsLadislav Peska0 Charles University in Prague, Faculty of Mathematics and Physics Our work is generally focused on recommending for small or medium-sized e-commerce portals, where explicit feedback is absent and thus the usage of implicit feedback is necessary. Nonetheless, for some implicit feedback features, the presentation context may be of high importance. In this paper, we present a model of relevant contextual features affecting user feedback, propose methods leveraging those features, publish a dataset of real e-commerce users containing multiple user feedback indicators as well as its context and finally present results of purchase prediction and recommendation experiments. Off-line experiments with real users of a Czech travel agency website corroborated the importance of leveraging presentation context in both purchase prediction and recommendation tasks.http://arxiv.org/pdf/1612.04978v1
collection DOAJ
language English
format Article
sources DOAJ
author Ladislav Peska
spellingShingle Ladislav Peska
Using the Context of User Feedback in Recommender Systems
Electronic Proceedings in Theoretical Computer Science
author_facet Ladislav Peska
author_sort Ladislav Peska
title Using the Context of User Feedback in Recommender Systems
title_short Using the Context of User Feedback in Recommender Systems
title_full Using the Context of User Feedback in Recommender Systems
title_fullStr Using the Context of User Feedback in Recommender Systems
title_full_unstemmed Using the Context of User Feedback in Recommender Systems
title_sort using the context of user feedback in recommender systems
publisher Open Publishing Association
series Electronic Proceedings in Theoretical Computer Science
issn 2075-2180
publishDate 2016-12-01
description Our work is generally focused on recommending for small or medium-sized e-commerce portals, where explicit feedback is absent and thus the usage of implicit feedback is necessary. Nonetheless, for some implicit feedback features, the presentation context may be of high importance. In this paper, we present a model of relevant contextual features affecting user feedback, propose methods leveraging those features, publish a dataset of real e-commerce users containing multiple user feedback indicators as well as its context and finally present results of purchase prediction and recommendation experiments. Off-line experiments with real users of a Czech travel agency website corroborated the importance of leveraging presentation context in both purchase prediction and recommendation tasks.
url http://arxiv.org/pdf/1612.04978v1
work_keys_str_mv AT ladislavpeska usingthecontextofuserfeedbackinrecommendersystems
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