Temporal-based Optimization to Solve Data Sparsity in Collaborative Filtering

Al-Hadi, Ismail Ahmed Al-Qasem; Alomari, Mohammad Ahmed; Alshari, Eissa M.; Ghanem, Waheed Ali H. M.; Ghaleb, Safwan M.

doi:10.14569/ijacsa.2020.0111262

Cited by 3 publications

(4 citation statements)

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“…In this study, the ReComS approach is proposed to predict the variables of the input setting according to the data history of the patient. As ReComS is expected to provide low prediction accuracy, it is integrated with a clustering method (as used in similar experimental works ( Al-Hadi et al, 2017 , 2020a )) and referred to as the ReComS+ approach. ReComS+ provides good prediction accuracy.…”

Section: Methodsmentioning

confidence: 99%

“…The proposed approaches are evaluated to examine the performance of the CF technique using RMSE ( Al-Hadi et al, 2020a ) and Mean Absolute Error (MAE) ( Wang, Yih & Ventresca, 2020 ). In this article, RMSE measure is used for calculating the differences between the variable of target patient and predicted values for same variables of target patient.…”

Section: Methodsmentioning

confidence: 99%

“…The use of CF (a popular technique in RSs) to send personalised recommendations to users based on their behaviour has become widely used due to its efficiency in recommending preferred items. CF technique utilises product ratings provided by a collection of customers and recommends products that the target customer has not yet considered but will likely enjoy ( Al-Hadi et al, 2020a ). The rating score (with a value between 1 and 5) is used to indicate if a person likes a product or otherwise.…”

Section: Definition Of Conceptsmentioning

confidence: 99%

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Improving patient rehabilitation performance in exercise games using collaborative filtering approach

Ismail

Al-Hadi

Groşan

et al. 2021

PeerJ Computer Science

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Background Virtual reality is utilised in exergames to help patients with disabilities improve on the movement of their limbs. Exergame settings, such as the game difficulty, play important roles in the rehabilitation outcome. Similarly, suboptimal exergames’ settings may adversely affect the accuracy of the results obtained. As such, the improvement in patients’ movement performances falls below the desired expectations. In this paper, a recommender system is incorporated to suggest the most preferred movement setting for each patient, based on the movement history of the patient. Method The proposed recommender system (ResComS) suggests the most suitable setting necessary to optimally improve patients’ rehabilitation performances. In the course of developing the recommender system, three methods are proposed and compared: ReComS (K-nearest neighbours and collaborative filtering algorithms), ReComS+ (k-means, K-nearest neighbours, and collaborative filtering algorithms) and ReComS++ (bacterial foraging optimisation, k-means, K-nearest neighbours, and collaborative filtering algorithms). The experimental datasets are collected using the Medical Interactive Recovery Assistant (MIRA) software platform. Result Experimental results, validated by the patients’ exergame performances, reveal that the ReComS++ approach predicts the best exergame settings for patients with 85.76% accuracy.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Definition Of Conceptsmentioning

confidence: 99%

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Improving patient rehabilitation performance in exercise games using collaborative filtering approach

Ismail

Al-Hadi

Groşan

et al. 2021

PeerJ Computer Science

Self Cite

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“…Additionally, in certain reaction conditions, the anticipated hexagonal TiB phase does not form as expected; instead, an orthorhombic layered TiB phase forms. 29 Miao et al, 2020 utilized a combination of evolutionary structure search and first-principles calculations to envisage stable layered ternary borides. Some identified compounds included Zr 2 PbB 2 , Zr 2 TlB 2 , Hf 2 SnB 2 , Hf 2 InB 2 , and Zr 2 InB 2 which adopt a Ti 2 InB 2 type of structure.…”

Section: Synthesis and Characterization Of Mbenesmentioning

confidence: 99%

Novel Two-Dimensional MBenes: Synthesis, Properties, and Energy Storage and Electrocatalytic Applications of Two-Dimensional Metal Borides

Tripathy

2024

ACS Appl. Eng. Mater.

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MBenes can be understood as a novel family of two-dimensional metal borides which are sandwich-like structures analogues to MXenes, fabricated from encrusted MAB phases that have attracted enormous interest in the area of physical science with more emphasis on nanomaterials. These materials due to exhibiting various fascinating characteristics are claimed to have a promising future, specifically in the field of energy storage and electrocatalytic applications. Other applications explored so far include biotechnological applications. However, MBenes have not been broadly explored, and the research available on these materials is inadequate. Moreover, various other probable characteristics and uses are waiting to be explored. The current review is based on a clear understanding of MBenes, followed by their most appropriate and technical classification. Progress on the synthetic procedures, characteristics, and applications of MBenes for energy storage applications and electrocatalysis has also been explored. Subsequent discussions on current issues associated with experimental synthesis and hypothetical calculations along with perceptions and predictions about MBenes are provided.

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