A systematic literature review of recent advances on context-aware recommender systems
Recommender systems are software mechanisms whose usage is to offer suggestions for different types of entities like products, services, or contacts that could be useful or interesting for a specific user. Other ways have been explored in the field to enhance the power of these systems by integratin...
| Autores: | , |
|---|---|
| Tipo de recurso: | artículo |
| Fecha de publicación: | 2024 |
| País: | España |
| Institución: | Universidad Autónoma de Madrid |
| Repositorio: | Biblos-e Archivo. Repositorio Institucional de la UAM |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:biblosearchi::fc664a041a117f1c9e3d8ed9a7af74d3 |
| Acceso en línea: | https://hdl.handle.net/10486/767360 https://dx.doi.org/10.1007/s10462-024-10939-4 |
| Access Level: | acceso abierto |
| Palabra clave: | Recommendation Systems Context Awareness Context Modeling Evaluation Informática |
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A systematic literature review of recent advances on context-aware recommender systemsMateos Masa, PabloBellogin Kouki, AlejandroRecommendation SystemsContext AwarenessContext ModelingEvaluationInformáticaRecommender systems are software mechanisms whose usage is to offer suggestions for different types of entities like products, services, or contacts that could be useful or interesting for a specific user. Other ways have been explored in the field to enhance the power of these systems by integrating the context as an additional attribute. This inclusion tries to extract the user preferences more accurately taking into account multiple components such as temporal, spatial, or social ones. Notwithstanding the magnitude of context-awareness in this area, the research community is in agreement with the lack of framework for context information and how to integrate it into recommender systems. Under this premise, this paper focuses on a comprehensive systematic literature review of the state-of-the-art recommendation techniques and their characteristics to benefit from contextual information. The following survey presents the following contributions as outcomes of our study: (i) determine a framework where multiple aspects are taken into account to have a clear definition of context representation, (ii) the techniques used to incorporate context, and (iii) the evaluation of these methods in terms of reproducibility and effectiveness. Our review also covers some crucial topics about context integration, classification of the contexts, application domains, and evaluation of the used datasets, metrics, and code implementations, where we observed clear shiftings in algorithmic and evaluation trends towards Neural Network approaches and ranking metrics, respectively. Just as importantly, future research opportunities and directions are exposed as final closure, standing out the exploitation of various data sources and the scalability and customization of existing solutionsThis work has been supported by grant PID2022-139131NB-I00 funded by MCIN/ AEI/10.13039/501100011033 and by “ERDF A way of making Europe”Springer NatureEscuela Politécnica SuperiorDepartamento de Ingeniería InformáticaGobierno de España20242024-11-16research articlehttp://purl.org/coar/resource_type/c_2df8fbb1VoRhttp://purl.org/coar/version/c_970fb48d4fbd8a85info:eu-repo/semantics/articleapplication/pdfhttps://hdl.handle.net/10486/767360https://dx.doi.org/10.1007/s10462-024-10939-4reponame:Biblos-e Archivo. Repositorio Institucional de la UAMinstname:Universidad Autónoma de MadridInglésengopen accesshttp://purl.org/coar/access_right/c_abf2Attribution 4.0 Internationalhttp://creativecommons.org/licenses/by/4.0/info:eu-repo/semantics/openAccessoai:dnet:biblosearchi::fc664a041a117f1c9e3d8ed9a7af74d32026-06-23T12:46:27Z |
| dc.title.none.fl_str_mv |
A systematic literature review of recent advances on context-aware recommender systems |
| title |
A systematic literature review of recent advances on context-aware recommender systems |
| spellingShingle |
A systematic literature review of recent advances on context-aware recommender systems Mateos Masa, Pablo Recommendation Systems Context Awareness Context Modeling Evaluation Informática |
| title_short |
A systematic literature review of recent advances on context-aware recommender systems |
| title_full |
A systematic literature review of recent advances on context-aware recommender systems |
| title_fullStr |
A systematic literature review of recent advances on context-aware recommender systems |
| title_full_unstemmed |
A systematic literature review of recent advances on context-aware recommender systems |
| title_sort |
A systematic literature review of recent advances on context-aware recommender systems |
| dc.creator.none.fl_str_mv |
Mateos Masa, Pablo Bellogin Kouki, Alejandro |
| author |
Mateos Masa, Pablo |
| author_facet |
Mateos Masa, Pablo Bellogin Kouki, Alejandro |
| author_role |
author |
| author2 |
Bellogin Kouki, Alejandro |
| author2_role |
author |
| dc.contributor.none.fl_str_mv |
Escuela Politécnica Superior Departamento de Ingeniería Informática Gobierno de España |
| dc.subject.none.fl_str_mv |
Recommendation Systems Context Awareness Context Modeling Evaluation Informática |
| topic |
Recommendation Systems Context Awareness Context Modeling Evaluation Informática |
| description |
Recommender systems are software mechanisms whose usage is to offer suggestions for different types of entities like products, services, or contacts that could be useful or interesting for a specific user. Other ways have been explored in the field to enhance the power of these systems by integrating the context as an additional attribute. This inclusion tries to extract the user preferences more accurately taking into account multiple components such as temporal, spatial, or social ones. Notwithstanding the magnitude of context-awareness in this area, the research community is in agreement with the lack of framework for context information and how to integrate it into recommender systems. Under this premise, this paper focuses on a comprehensive systematic literature review of the state-of-the-art recommendation techniques and their characteristics to benefit from contextual information. The following survey presents the following contributions as outcomes of our study: (i) determine a framework where multiple aspects are taken into account to have a clear definition of context representation, (ii) the techniques used to incorporate context, and (iii) the evaluation of these methods in terms of reproducibility and effectiveness. Our review also covers some crucial topics about context integration, classification of the contexts, application domains, and evaluation of the used datasets, metrics, and code implementations, where we observed clear shiftings in algorithmic and evaluation trends towards Neural Network approaches and ranking metrics, respectively. Just as importantly, future research opportunities and directions are exposed as final closure, standing out the exploitation of various data sources and the scalability and customization of existing solutions |
| publishDate |
2024 |
| dc.date.none.fl_str_mv |
2024 2024-11-16 |
| dc.type.none.fl_str_mv |
research article http://purl.org/coar/resource_type/c_2df8fbb1 VoR http://purl.org/coar/version/c_970fb48d4fbd8a85 |
| dc.type.openaire.fl_str_mv |
info:eu-repo/semantics/article |
| format |
article |
| dc.identifier.none.fl_str_mv |
https://hdl.handle.net/10486/767360 https://dx.doi.org/10.1007/s10462-024-10939-4 |
| url |
https://hdl.handle.net/10486/767360 https://dx.doi.org/10.1007/s10462-024-10939-4 |
| dc.language.none.fl_str_mv |
Inglés eng |
| language_invalid_str_mv |
Inglés |
| language |
eng |
| dc.rights.none.fl_str_mv |
open access http://purl.org/coar/access_right/c_abf2 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
| dc.rights.openaire.fl_str_mv |
info:eu-repo/semantics/openAccess |
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open access http://purl.org/coar/access_right/c_abf2 Attribution 4.0 International http://creativecommons.org/licenses/by/4.0/ |
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openAccess |
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application/pdf |
| dc.publisher.none.fl_str_mv |
Springer Nature |
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Springer Nature |
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reponame:Biblos-e Archivo. Repositorio Institucional de la UAM instname:Universidad Autónoma de Madrid |
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Universidad Autónoma de Madrid |
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Biblos-e Archivo. Repositorio Institucional de la UAM |
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Biblos-e Archivo. Repositorio Institucional de la UAM |
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15,228081 |