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A Hybrid Recommender System for HCI Design Pattern Recommendations
| Content Provider | MDPI |
|---|---|
| Author | Buendía, Félix Braham, Amani Khemaja, Maha Gargouri, Faiez |
| Copyright Year | 2021 |
| 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. |
| Starting Page | 10776 |
| e-ISSN | 20763417 |
| DOI | 10.3390/app112210776 |
| Journal | Applied Sciences |
| Issue Number | 22 |
| Volume Number | 11 |
| Language | English |
| Publisher | MDPI |
| Publisher Date | 2021-11-15 |
| Access Restriction | Open |
| Subject Keyword | Applied Sciences Information and Library Science Hci Design Patterns Design Problems Semantic Similarity Ontology Models Recommender System |
| Content Type | Text |
| Resource Type | Article |
