دورية أكاديمية

Post-hoc recommendation explanations through an efficient exploitation of the DBpedia category hierarchy

التفاصيل البيبلوغرافية
العنوان: Post-hoc recommendation explanations through an efficient exploitation of the DBpedia category hierarchy
المؤلفون: Du, Yu, Ranwez, Sylvie, Sutton-Charani, Nicolas, Ranwez, Vincent
المساهمون: EuroMov - Digital Health in Motion (Euromov DHM), IMT - MINES ALES (IMT - MINES ALES), Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT)-Université de Montpellier (UM), Amélioration génétique et adaptation des plantes méditerranéennes et tropicales (UMR AGAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Université de Montpellier (UM)
المصدر: ISSN: 0950-7051.
بيانات النشر: HAL CCSD
Elsevier
سنة النشر: 2022
مصطلحات موضوعية: Linked Open Data (LOD), Knowledge graph, Recommender system, Recommendation explanation, DBpedia, Ontology, [SPI]Engineering Sciences [physics], [INFO]Computer Science [cs]
الوصف: International audience ; Leveraging knowledge graphs for post-hoc recommendation explanations has been investigated in recent years. Existing approaches rely mainly on the overlap properties (encoded by knowledge graphs) that characterize both user liked items and the recommended ones. These approaches, however, do not fully leverage the property hierarchy of knowledge graphs which may lead to flawed explanations. In this paper we introduce an approach that takes the whole property hierarchy into account. This is done with a limited computation time overhead thanks to efficient algorithmic optimizations relying on sub-ontology extraction. The hierarchical relationships among properties are also considered to avoid redundant properties for explanation. We carried out a user study of 155 participants in the movie recommendation domain and used both offline and online metrics to assess the proposed approach. Significant improvements, in terms of informativeness (by 39%), persuasiveness (by 22%), engagement (by 29%) and user trust (by 26%), are suggested by the obtained results, as compared to the state-of-the-art property-based explanation model. Our findings indicate the superiority of accounting for the whole property hierarchy when dealing with post-hoc recommendation explanations.
نوع الوثيقة: article in journal/newspaper
اللغة: English
العلاقة: hal-03623354; https://imt-mines-ales.hal.science/hal-03623354Test; https://imt-mines-ales.hal.science/hal-03623354/documentTest; https://imt-mines-ales.hal.science/hal-03623354/file/1-s2.0-S0950705122002490-main.pdfTest
DOI: 10.1016/j.knosys.2022.108560
الإتاحة: https://doi.org/10.1016/j.knosys.2022.108560Test
https://imt-mines-ales.hal.science/hal-03623354Test
https://imt-mines-ales.hal.science/hal-03623354/documentTest
https://imt-mines-ales.hal.science/hal-03623354/file/1-s2.0-S0950705122002490-main.pdfTest
حقوق: http://creativecommons.org/licenses/by-nc-ndTest/ ; info:eu-repo/semantics/OpenAccess
رقم الانضمام: edsbas.A7FB5EF4
قاعدة البيانات: BASE