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Triyanna Widiyaningtyas, Muhammad Iqbal Ardiansyah and Teguh Bharata Adji
One of the most prevalent recommendation systems is ranking-oriented collaborative filtering which employs ranking aggregation. The collaborative filtering study recently applied the ranking aggregation that considers the weight point of items to achieve...
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Aisha Sikder and Andreas Züfle
Singular value decomposition (SVD) is ubiquitously used in recommendation systems to estimate and predict values based on latent features obtained through matrix factorization. But, oblivious of location information, SVD has limitations in predicting var...
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Sandra L. Gomez-Coronel, Ernesto Moya-Albor, Jorge Brieva and Andrés Romero-Arellano
Currently, algorithms to embed watermarks into digital images are increasing exponentially, for example in image copyright protection. However, when a watermarking algorithm is applied, the preservation of the image?s quality is of utmost importance, for...
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Siriwan Intawichai and Saifon Chaturantabut
An accelerated least-squares approach is introduced in this work by incorporating a greedy point selection method with randomized singular value decomposition (rSVD) to reduce the computational complexity of missing data reconstruction. The rSVD is used ...
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Ali M. Ahmed Al Sabaawi,Hacer Karacan,Yusuf Erkan Yenice
Pág. pp. 70 - 87
Recently, Recommender Systems (RSs) have attracted many researchers whose goal is to improve the performance of the prediction accuracy of recommendation systems by alleviating RSs drawbacks. The most common limitations are sparsity and the cold-start pr...
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Renato Tampol, Hector M. Aguiling
Pág. 231 - 240
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Renato Tampol, Hector M. Aguiling
Pág. 231 - 240
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Athanasios Alexopoulos, Georgios Drakopoulos, Andreas Kanavos, Phivos Mylonas and Gerasimos Vonitsanos
At the dawn of the 10V or big data data era, there are a considerable number of sources such as smart phones, IoT devices, social media, smart city sensors, as well as the health care system, all of which constitute but a small portion of the data lakes ...
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Laurens Bogaardt, Romulo Goncalves, Raul Zurita-Milla and Emma Izquierdo-Verdiguier
The Singular Value Decomposition (SVD) is a mathematical procedure with multiple applications in the geosciences. For instance, it is used in dimensionality reduction and as a support operator for various analytical tasks applicable to spatio-temporal da...
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Heng Zhang, Chengyou Wang and Xiao Zhou
With the development of image processing technology, the copyright protection of digital images has become an urgent problem to be solved. As an effective method, the robust digital watermarking technique emerges at a historic moment. Currently, most rob...
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Yunpeng Zhang, Chengyou Wang, Xiaoli Wang and Min Wang
Watermarking techniques can be applied in digital images to maintain the authenticity and integrity for copyright protection. In this paper, scale-invariant feature transform (SIFT) is combined with local digital watermarking and a digital watermarking a...
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Heng Zhang, Chengyou Wang and Xiao Zhou
With the development of image processing technology, the copyright protection of digital images has become an urgent problem to be solved. As an effective method, the robust digital watermarking technique emerges at a historic moment. Currently, most rob...
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Yunpeng Zhang, Chengyou Wang, Xiaoli Wang and Min Wang
Watermarking techniques can be applied in digital images to maintain the authenticity and integrity for copyright protection. In this paper, scale-invariant feature transform (SIFT) is combined with local digital watermarking and a digital watermarking a...
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Mahbuba Begum, Sumaita Binte Shorif, Mohammad Shorif Uddin, Jannatul Ferdush, Tony Jan, Alistair Barros and Md Whaiduzzaman
Digital multimedia elements such as text, image, audio, and video can be easily manipulated because of the rapid rise of multimedia technology, making data protection a prime concern. Hence, copyright protection, content authentication, and integrity ver...
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Andres Gallego, Francisco Roman and Edwin Pineda
In this paper, we obtain the Complex Natural Resonances of an object from the backscattered response in the frequency domain with a novel rational function approximation method based on both Vector Fitting and Cauchy methods. We determine the system orde...
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Mohammed Isam Al-Hiyali, Norashikin Yahya, Ibrahima Faye, Maged S. Al-Quraishi and Abdulhakim Al-Ezzi
The study of functional connectivity (FC) of the brain using resting-state functional magnetic resonance imaging (rs-fMRI) has gained traction for uncovering FC patterns related to autism spectrum disorder (ASD). It is believed that the neurodynamic comp...
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Jialu Sui and Jian Yin
Nowadays, as the number of items is increasing and the number of items that users have access to is limited, user-item preference matrices in recommendation systems are always sparse. This leads to a data sparsity problem. The latent factor analysis (LFA...
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Mahbuba Begum and Mohammad Shorif Uddin
Digital image authentication is an extremely significant concern for the digital revolution, as it is easy to tamper with any image. In the last few decades, it has been an urgent concern for researchers to ensure the authenticity of digital images. Base...
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Shuting Cai, Qilun Luo, Ming Yang, Wen Li and Mingqing Xiao
Tensor Robust Principal Component Analysis (TRPCA) plays a critical role in handling high multi-dimensional data sets, aiming to recover the low-rank and sparse components both accurately and efficiently. In this paper, different from current approach, w...
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Yuyu Yuan, Ahmed Zahir and Jincui Yang
Recommendation systems often use side information to both alleviate problems, such as the cold start problem and data sparsity, and increase prediction accuracy. One such piece of side information, which has been widely investigated in addressing such ch...
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