A Hybrid Recommender System for HCI Design Pattern Recommendations

User interface design patterns are acknowledged as a standard solution to recurring design problems. The heterogeneity of existing design patterns makes the selection of relevant ones difficult. To tackle these concerns, the current work contributes in a twofold manner. The first contribution is the...

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Autores principales:	Amani Braham, Maha Khemaja, Félix Buendía, Faiez Gargouri
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	HCI design patterns design problems semantic similarity ontology models recommender system Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/93ffbb0e7aad4b85aca710d7e8240251
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id	oai:doaj.org-article:93ffbb0e7aad4b85aca710d7e8240251
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spelling	oai:doaj.org-article:93ffbb0e7aad4b85aca710d7e82402512021-11-25T16:37:51ZA Hybrid Recommender System for HCI Design Pattern Recommendations10.3390/app1122107762076-3417https://doaj.org/article/93ffbb0e7aad4b85aca710d7e82402512021-11-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/22/10776https://doaj.org/toc/2076-3417User interface design patterns are acknowledged as a standard solution to recurring design problems. The heterogeneity of existing design patterns makes the selection of relevant ones difficult. To tackle these concerns, the current work contributes in a twofold manner. The first contribution is the development of a recommender system for selecting the most relevant design patterns in the Human Computer Interaction (HCI) domain. This system introduces a hybrid approach that combines text-based and ontology-based techniques and is aimed at using semantic similarity along with ontology models to retrieve appropriate HCI design patterns. The second contribution addresses the validation of the proposed recommender system regarding the acceptance intention towards our system by assessing the perceived experience and the perceived accuracy. To this purpose, we conducted a user-centric evaluation experiment wherein participants were invited to fill pre-study and post-test questionnaires. The findings of the evaluation study revealed that the perceived experience of the proposed system’s quality and the accuracy of the recommended design patterns were assessed positively.Amani BrahamMaha KhemajaFélix BuendíaFaiez GargouriMDPI AGarticleHCIdesign patternsdesign problemssemantic similarityontology modelsrecommender systemTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 10776, p 10776 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	HCI design patterns design problems semantic similarity ontology models recommender system Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	HCI design patterns design problems semantic similarity ontology models recommender system Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Amani Braham Maha Khemaja Félix Buendía Faiez Gargouri A Hybrid Recommender System for HCI Design Pattern Recommendations
description	User interface design patterns are acknowledged as a standard solution to recurring design problems. The heterogeneity of existing design patterns makes the selection of relevant ones difficult. To tackle these concerns, the current work contributes in a twofold manner. The first contribution is the development of a recommender system for selecting the most relevant design patterns in the Human Computer Interaction (HCI) domain. This system introduces a hybrid approach that combines text-based and ontology-based techniques and is aimed at using semantic similarity along with ontology models to retrieve appropriate HCI design patterns. The second contribution addresses the validation of the proposed recommender system regarding the acceptance intention towards our system by assessing the perceived experience and the perceived accuracy. To this purpose, we conducted a user-centric evaluation experiment wherein participants were invited to fill pre-study and post-test questionnaires. The findings of the evaluation study revealed that the perceived experience of the proposed system’s quality and the accuracy of the recommended design patterns were assessed positively.
format	article
author	Amani Braham Maha Khemaja Félix Buendía Faiez Gargouri
author_facet	Amani Braham Maha Khemaja Félix Buendía Faiez Gargouri
author_sort	Amani Braham
title	A Hybrid Recommender System for HCI Design Pattern Recommendations
title_short	A Hybrid Recommender System for HCI Design Pattern Recommendations
title_full	A Hybrid Recommender System for HCI Design Pattern Recommendations
title_fullStr	A Hybrid Recommender System for HCI Design Pattern Recommendations
title_full_unstemmed	A Hybrid Recommender System for HCI Design Pattern Recommendations
title_sort	hybrid recommender system for hci design pattern recommendations
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/93ffbb0e7aad4b85aca710d7e8240251
work_keys_str_mv	AT amanibraham ahybridrecommendersystemforhcidesignpatternrecommendations AT mahakhemaja ahybridrecommendersystemforhcidesignpatternrecommendations AT felixbuendia ahybridrecommendersystemforhcidesignpatternrecommendations AT faiezgargouri ahybridrecommendersystemforhcidesignpatternrecommendations AT amanibraham hybridrecommendersystemforhcidesignpatternrecommendations AT mahakhemaja hybridrecommendersystemforhcidesignpatternrecommendations AT felixbuendia hybridrecommendersystemforhcidesignpatternrecommendations AT faiezgargouri hybridrecommendersystemforhcidesignpatternrecommendations
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A Hybrid Recommender System for HCI Design Pattern Recommendations

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