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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| Format: | Article |
| Language: | English |
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Open Publishing Association
2016-12-01
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| Series: | Electronic Proceedings in Theoretical Computer Science |
| Online Access: | http://arxiv.org/pdf/1612.04978v1 |
| _version_ | 1811275154149343232 |
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| author | Ladislav Peska |
| author_facet | Ladislav Peska |
| author_sort | Ladislav Peska |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-04-12T23:32:59Z |
| format | Article |
| id | doaj.art-a648016590de4d0f88de3ff12e823c8b |
| institution | Directory Open Access Journal |
| issn | 2075-2180 |
| language | English |
| last_indexed | 2024-04-12T23:32:59Z |
| publishDate | 2016-12-01 |
| publisher | Open Publishing Association |
| record_format | Article |
| series | Electronic Proceedings in Theoretical Computer Science |
| spelling | doaj.art-a648016590de4d0f88de3ff12e823c8b2022-12-22T03:12:13ZengOpen 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 |
| spellingShingle | Ladislav Peska Using the Context of User Feedback in Recommender Systems Electronic Proceedings in Theoretical Computer Science |
| title | 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_short | Using the Context of User Feedback in Recommender Systems |
| title_sort | using the context of user feedback in recommender systems |
| url | http://arxiv.org/pdf/1612.04978v1 |
| work_keys_str_mv | AT ladislavpeska usingthecontextofuserfeedbackinrecommendersystems |