Evolutionary Approach for Building, Exploring and Recommending Complex Items With Application in Nutritional Interventions
Over the last few years, the ability of recommender systems to help us in different environments has been increasing. Several systems try to offer solutions in highly complex environments such as nutrition, housing, or traveling. In this paper, we present a recommendation system capable of using dif...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2023-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/10168109/ |
| _version_ | 1797785082217365504 |
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| author | Bartolome Ortiz-Viso Andrea Morales-Garzon Maria J. Martin-Bautista Maria-Amparo Vila |
| author_facet | Bartolome Ortiz-Viso Andrea Morales-Garzon Maria J. Martin-Bautista Maria-Amparo Vila |
| author_sort | Bartolome Ortiz-Viso |
| collection | DOAJ |
| description | Over the last few years, the ability of recommender systems to help us in different environments has been increasing. Several systems try to offer solutions in highly complex environments such as nutrition, housing, or traveling. In this paper, we present a recommendation system capable of using different input sources (data and knowledge-based) and producing a complex structured output. We have used an evolutionary approach to combine several unitary items within a flexible structure and have built an initial set of complex configurable items. Then, a content-based approach refines (in terms of preferences) these candidates to offer a final recommendation. We conclude with the application of this approach to the healthy diet recommendation problem, addressing its strengths in this domain. |
| first_indexed | 2024-03-13T00:49:06Z |
| format | Article |
| id | doaj.art-1aa06d6ff1d2493f801061b40de1e38a |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-03-13T00:49:06Z |
| publishDate | 2023-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-1aa06d6ff1d2493f801061b40de1e38a2023-07-07T23:00:24ZengIEEEIEEE Access2169-35362023-01-0111658916590510.1109/ACCESS.2023.329091810168109Evolutionary Approach for Building, Exploring and Recommending Complex Items With Application in Nutritional InterventionsBartolome Ortiz-Viso0https://orcid.org/0000-0003-2181-0734Andrea Morales-Garzon1Maria J. Martin-Bautista2Maria-Amparo Vila3Department of Computer Science and Artificial Intelligence, University of Granada, Granada, SpainDepartment of Computer Science and Artificial Intelligence, University of Granada, Granada, SpainDepartment of Computer Science and Artificial Intelligence, University of Granada, Granada, SpainDepartment of Computer Science and Artificial Intelligence, University of Granada, Granada, SpainOver the last few years, the ability of recommender systems to help us in different environments has been increasing. Several systems try to offer solutions in highly complex environments such as nutrition, housing, or traveling. In this paper, we present a recommendation system capable of using different input sources (data and knowledge-based) and producing a complex structured output. We have used an evolutionary approach to combine several unitary items within a flexible structure and have built an initial set of complex configurable items. Then, a content-based approach refines (in terms of preferences) these candidates to offer a final recommendation. We conclude with the application of this approach to the healthy diet recommendation problem, addressing its strengths in this domain.https://ieeexplore.ieee.org/document/10168109/Applied computingcomplex recommendation systemshuman-computer interactioninformation retrievalrecommendation systems |
| spellingShingle | Bartolome Ortiz-Viso Andrea Morales-Garzon Maria J. Martin-Bautista Maria-Amparo Vila Evolutionary Approach for Building, Exploring and Recommending Complex Items With Application in Nutritional Interventions IEEE Access Applied computing complex recommendation systems human-computer interaction information retrieval recommendation systems |
| title | Evolutionary Approach for Building, Exploring and Recommending Complex Items With Application in Nutritional Interventions |
| title_full | Evolutionary Approach for Building, Exploring and Recommending Complex Items With Application in Nutritional Interventions |
| title_fullStr | Evolutionary Approach for Building, Exploring and Recommending Complex Items With Application in Nutritional Interventions |
| title_full_unstemmed | Evolutionary Approach for Building, Exploring and Recommending Complex Items With Application in Nutritional Interventions |
| title_short | Evolutionary Approach for Building, Exploring and Recommending Complex Items With Application in Nutritional Interventions |
| title_sort | evolutionary approach for building exploring and recommending complex items with application in nutritional interventions |
| topic | Applied computing complex recommendation systems human-computer interaction information retrieval recommendation systems |
| url | https://ieeexplore.ieee.org/document/10168109/ |
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