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Hybrid Recommender System via Personalized Users’ Context
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| Zeitschriftentitel: | Cybernetics and Information Technologies |
|---|---|
| Personen und Körperschaften: | , , |
| In: | Cybernetics and Information Technologies, 19, 2019, 1, S. 101-115 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Walter de Gruyter GmbH
|
| Schlagwörter: |
| author_facet |
Nosshi, Anthony Asem, Aziza Senousy, Mohamed Badr Nosshi, Anthony Asem, Aziza Senousy, Mohamed Badr |
|---|---|
| author |
Nosshi, Anthony Asem, Aziza Senousy, Mohamed Badr |
| spellingShingle |
Nosshi, Anthony Asem, Aziza Senousy, Mohamed Badr Cybernetics and Information Technologies Hybrid Recommender System via Personalized Users’ Context General Computer Science |
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nosshi, anthony |
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Nosshi, Anthony Asem, Aziza Senousy, Mohamed Badr 1314-4081 Walter de Gruyter GmbH General Computer Science http://dx.doi.org/10.2478/cait-2019-0006 <jats:title>Abstract</jats:title> <jats:p>In movie domain, finding the appropriate movie to watch is a challenging task. This paper proposes a recommender system that suggests movies in cinema that fit the user’s available time, location, mood and emotions. Conducted experiments for evaluation showed that the proposed method outperforms the other baselines.</jats:p> Hybrid Recommender System via Personalized Users’ Context Cybernetics and Information Technologies |
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Walter de Gruyter GmbH, 2019 |
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Walter de Gruyter GmbH, 2019 |
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Walter de Gruyter GmbH |
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Cybernetics and Information Technologies |
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| title |
Hybrid Recommender System via Personalized Users’ Context |
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Hybrid Recommender System via Personalized Users’ Context |
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Hybrid Recommender System via Personalized Users’ Context |
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Hybrid Recommender System via Personalized Users’ Context |
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Hybrid Recommender System via Personalized Users’ Context |
| title_short |
Hybrid Recommender System via Personalized Users’ Context |
| title_sort |
hybrid recommender system via personalized users’ context |
| topic |
General Computer Science |
| url |
http://dx.doi.org/10.2478/cait-2019-0006 |
| publishDate |
2019 |
| physical |
101-115 |
| description |
<jats:title>Abstract</jats:title>
<jats:p>In movie domain, finding the appropriate movie to watch is a challenging task. This paper proposes a recommender system that suggests movies in cinema that fit the user’s available time, location, mood and emotions. Conducted experiments for evaluation showed that the proposed method outperforms the other baselines.</jats:p> |
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| author | Nosshi, Anthony, Asem, Aziza, Senousy, Mohamed Badr |
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| description | <jats:title>Abstract</jats:title> <jats:p>In movie domain, finding the appropriate movie to watch is a challenging task. This paper proposes a recommender system that suggests movies in cinema that fit the user’s available time, location, mood and emotions. Conducted experiments for evaluation showed that the proposed method outperforms the other baselines.</jats:p> |
| doi_str_mv | 10.2478/cait-2019-0006 |
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| imprint | Walter de Gruyter GmbH, 2019 |
| imprint_str_mv | Walter de Gruyter GmbH, 2019 |
| institution | DE-D161, DE-Zwi2, DE-Gla1, DE-Zi4, DE-15, DE-Pl11, DE-Rs1, DE-105, DE-14, DE-Ch1, DE-L229, DE-D275, DE-Bn3, DE-Brt1 |
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| physical | 101-115 |
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| series | Cybernetics and Information Technologies |
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| spelling | Nosshi, Anthony Asem, Aziza Senousy, Mohamed Badr 1314-4081 Walter de Gruyter GmbH General Computer Science http://dx.doi.org/10.2478/cait-2019-0006 <jats:title>Abstract</jats:title> <jats:p>In movie domain, finding the appropriate movie to watch is a challenging task. This paper proposes a recommender system that suggests movies in cinema that fit the user’s available time, location, mood and emotions. Conducted experiments for evaluation showed that the proposed method outperforms the other baselines.</jats:p> Hybrid Recommender System via Personalized Users’ Context Cybernetics and Information Technologies |
| spellingShingle | Nosshi, Anthony, Asem, Aziza, Senousy, Mohamed Badr, Cybernetics and Information Technologies, Hybrid Recommender System via Personalized Users’ Context, General Computer Science |
| title | Hybrid Recommender System via Personalized Users’ Context |
| title_full | Hybrid Recommender System via Personalized Users’ Context |
| title_fullStr | Hybrid Recommender System via Personalized Users’ Context |
| title_full_unstemmed | Hybrid Recommender System via Personalized Users’ Context |
| title_short | Hybrid Recommender System via Personalized Users’ Context |
| title_sort | hybrid recommender system via personalized users’ context |
| title_unstemmed | Hybrid Recommender System via Personalized Users’ Context |
| topic | General Computer Science |
| url | http://dx.doi.org/10.2478/cait-2019-0006 |