scholarly journals A Hybrid Recommender System for HCI Design Pattern Recommendations

2021 ◽  
Vol 11 (22) ◽  
pp. 10776
Author(s):  
Amani Braham ◽  
Maha Khemaja ◽  
Félix Buendía ◽  
Faiez Gargouri
Keyword(s):  
Recommender System ◽  
Interface Design ◽  
Design Patterns ◽  
Hybrid Approach ◽  
Evaluation Study ◽  
Design Problems ◽  
Post Test ◽  
Standard Solution ◽  
Hybrid Recommender ◽  
Selection Of

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.

DESIGNING HYPERMEDIA APPLICATIONS WITH OBJECTS AND PATTERNS

1999 ◽  
Vol 09 (06) ◽  
pp. 745-766 ◽  
Author(s):  
GUSTAVO ROSSI ◽  
DANIEL SCHWABE ◽  
FERNANDO LYARDET
Keyword(s):  
Interface Design ◽  
Design Patterns ◽  
Design Method ◽  
Object Oriented ◽  
Design Problems ◽  
Hypermedia Design ◽  
High Level ◽  
Abstract Interface ◽  
Interface Structures ◽  
Hypermedia Applications

In this paper we present a software engineering approach for building hypermedia applications. Our approach combines the use of an object-oriented method with a system of design patterns for navigational and interface design. We first present the core activities in the Object-Oriented Hypermedia Design Method (OOHDM), namely conceptual design navigation design, abstract interface design and implementation, describing the modeling constructs we use to build high-level, abstract navigational and interface structures. Next we give the rationale for using design patterns in the process of building high quality hypermedia applications, and present some simple patterns solving recurrent design problems. We finally discuss some further issues.

A Hybrid Recommender System for Rating Prediction of Arabic Reviews

2020 ◽  
pp. 2050010
Author(s):  
Fouzi Harrag ◽  
Abdulmalik Salman Al-Salman ◽  
Alaa Alquahtani
Keyword(s):  
Sentiment Analysis ◽  
Recommender Systems ◽  
Recommender System ◽  
Opinion Mining ◽  
Good Accuracy ◽  
Hybrid Approach ◽  
Data Sparsity ◽  
Hybrid Recommender System ◽  
Rating Prediction ◽  
Hybrid Recommender

Recommender systems nowadays are playing an important role in the delivery of services and information to users. Sentiment analysis (also known as opinion mining) is the process of determining the attitude of textual opinions, whether they are positive, negative or neutral. Data sparsity is representing a big issue for recommender systems because of the insufficiency of user rating or absence of data about users or items. This research proposed a hybrid approach combining sentiment analysis and recommender systems to tackle the problem of data sparsity problems by predicting the rating of products from users’ reviews using text mining and NLP techniques. This research focuses especially on Arabic reviews, where the model is evaluated using Opinion Corpus for Arabic (OCA) dataset. Our system was efficient, and it showed a good accuracy of nearly 85% in predicting the rating from reviews.

Ontology Supported Hybrid Recommender System With Threshold Based Nearest Neighbourhood Approach

2019 ◽  
Vol 15 (2) ◽  
pp. 85-107
Author(s):  
Zameer Gulzar ◽  
L. Arun Raj ◽  
A. Anny Leema
Keyword(s):  
Recommender System ◽  
Hybrid Approach ◽  
Learning Systems ◽  
E Learning ◽  
Hybrid Recommender System ◽  
The Individual ◽  
Hybrid Recommender ◽  
Nearest Neighborhood ◽  
Personal Interests ◽  
Hybrid Methodology

Traditional e-learning systems lack the personalization feature to guide learners for selecting the most suitable courses needed. Choosing appropriate courses in the seminal years is important for a future learner who depends on such decisions, as selecting the wrong courses means a mismatch between learner's capability and personal interests. Therefore, a recommender system was developed to suggest and direct the students in selecting the appropriate courses. This study presents algorithms to personalize courses for scholars based on their interests to make learning effective and more productive. The hybrid methodology has been used to retrieve useful information and make accurate recommendations to help learners to increase their performance and improve their satisfaction level. The results suggest that a hybrid approach is better as it will enjoy all the advantages of the individual recommender systems and mitigate their limitations. A threshold-based nearest neighborhood approach will further strengthen the proposed system by finding a similar learner for targeted learners.

Work Models for Interface Design: Techniques and Applications in Complex Domains

1998 ◽  
Vol 42 (3) ◽  
pp. 335-335
Author(s):  
Kim J. Vicente
Keyword(s):  
Interface Design ◽  
Work Environments ◽  
Cognitive Engineering ◽  
Modeling Tools ◽  
Design Problems ◽  
Analysis Techniques ◽  
Modeling Techniques ◽  
Human Operators ◽  
Community Modeling ◽  
Selection Of

The modeling of human work is ubiquitous in the cognitive engineering community. Modeling can take many diverse forms, but its goal is always the same: to provide designers with a deeper understanding of the needs of human operators. This understanding becomes ever more critical as work domains increase in complexity because the capability of designers to anticipate all of the needs in all possible contexts becomes less tenable without modeling tools. Why, then, is there such a proliferation of work analysis techniques? Even more importantly, which modeling techniques are most useful for what types of design problems? In this symposium, several papers will be presented describing the application of various modeling techniques to the design of complex work environments. An emphasis will be placed on identifying the modeling techniques that are useful, or not useful, for various types of application domains and for different design goals. The strengths of integrated modeling techniques will be examined as compared with their increased costs. The various presenters will provide guidance for the selection of design problems, the application and payoffs from the modeling effort, and the use of results for design.

Toward a Hybrid Recommender System for E-learning Personnalization Based on Data Mining Techniques

2018 ◽  
Vol 2 (4) ◽  
pp. 271 ◽  
Author(s):  
Outmane Bourkoukou ◽  
Essaid El Bachari
Keyword(s):  
Learning Style ◽  
Recommender System ◽  
Adaptive Learning ◽  
Learning Objects ◽  
Research Field ◽  
Learning System ◽  
K Nearest Neighbors ◽  
E Learning ◽  
Hybrid Recommender System ◽  
Hybrid Recommender

Personalized courseware authoring based on recommender system, which is the process of automatic learning objects selecting and sequencing, is recognized as one of the most interesting research field in intelligent web-based education. Since the learner’s profile of each learner is different from one to another, we must fit learning to the different needs of learners. In fact from the knowledge of the learner’s profile, it is easier to recommend a suitable set of learning objects to enhance the learning process. In this paper we describe a new adaptive learning system-LearnFitII, which can automatically adapt to the dynamic preferences of learners. This system recognizes different patterns of learning style and learners’ habits through testing the psychological model of learners and mining their server logs. Firstly, the device proposed a personalized learning scenario to deal with the cold start problem by using the Felder and Silverman’s model. Next, it analyzes the habits and the preferences of the learners through mining the information about learners’ actions and interactions. Finally, the learning scenario is revisited and updated using hybrid recommender system based on K-Nearest Neighbors and association rule mining algorithms. The results of the system tested in real environments show that considering the learner’s preferences increases learning quality and satisfies the learner.

scholarly journals Didactic Model: Teaching the English Temporal System to Arabic Freshman Learners of English

2017 ◽  
Vol 19 (_sup1) ◽  
pp. 81-97
Author(s):  
Thana Hmidani
Keyword(s):  
Linguistic Competence ◽  
First Year ◽  
Language Awareness ◽  
Intensive English ◽  
First Year Students ◽  
Medical College ◽  
Temporal System ◽  
Post Test ◽  
And Control ◽  
Selection Of

This study took place at a medical college with 57 Arabic first-year students taking an intensive English course. The aim was to address the problems that learners experience when using the English tenses properly. The didactic model was developed and implemented in the study group only (27 students). Pre, mid-, and post-tests were administered to study and control groups at three points in time. The model is a selection of aspects from different methods combined aiming to lead participants to a higher level of linguistic competence in terms of language awareness, reading and writing skills, and vocubulary building. The results indicated statistically significant differences in the post-test between the two groups over time regarding the level of linguistic competence.

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