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Gorge: graph convolutional networks on heterogeneous multi-relational graphs for polypharmacy side effect prediction
Determining the side effects of multidrug combinations is a very important issue in drug risk studies. However, designing clinical trials to...
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DeepRS: A Library of Recommendation Algorithms Based on Deep Learning
In recent years, recommendation systems have become more complex with increasing research on user preferences. Recommendation algorithm based on deep...
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Deep Learning Model Optimization
This chapter reviews recent work on compressing and accelerating deep neural networks, which has attracted much attention from the deep learning...
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Z-NetMF: A Biased Embedding Method Based on Matrix Factorization
Network embedding represents the graph in low dimensions, improving the processing of big scale tasks. As node2vec can only be modeled as a tensor,...
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Feature Learning of Patent Networks Using Tensor Decomposition
In the age of big data, the graph clustering algorithms are visual analytics can help the decision-makers to have a precise description of the...
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Knowledge graph–enabled tolerancing experience acquisition and reuse for tolerance specification
In product design, tolerance specification is a crucial process of specifying appropriate tolerance types and values on mechanical parts to control...
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Time-Aware Online QoS Prediction Using LSTM and Non-negative Matrix Factorization
In the present technological world, users access various cloud services directly or indirectly around the clock. Hence, availability is not just...
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Comparison and Performance Evaluation of Fusion Mechanism for Audio–Video Based Multimodal Emotion Recognition
Artificial emotional intelligence is an emerging research area in artificial intelligence. In artificial intelligence, machine learning and deep...
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Multidimensional clinical data denoising via Bayesian CP factorization
CANDECOMP/PARAFAC (CP) tensor factorization is an efficient technique for incomplete tensor-data processing through capturing the multilinear latent...
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A Framework Based on Latent Neighbourhood and Tensor Based Method for Recommender System
Recommendation systems are highly used in the online shop** websites, movie websites etc. Many techniques are developed for the item recommendation...
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Transport Object Detection in Street View Imagery Using Decomposed Convolutional Neural Networks
Deep learning has achieved great successes in performing many visual recognition tasks including object detection. Nevertheless, existing deep...
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Twitter Spatio-temporal Topic Dynamics and Sentiment Analysis During the First COVID-19 Lockdown in India
The advent of COVID-19 has tremendously affected the global economy. More people have suffered, and some of them even lost their lives. As the worst...
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Tensor Decomposition Based Electrical Data Recovery
As the development of smart grid and energy internet, the amount of transmitted data in real time significantly increase. Due to the mismatch with...
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A dynamic hypergraph regularized non-negative tucker decomposition framework for multiway data analysis
Non-negative tensor decomposition has achieved significant success in machine learning due to its superiority in extracting the non-negative...
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Enhancing the aggregate diversity with mutual trust computations for context-aware recommendations
Context-aware Recommender Systems (CARS) deal with modeling and prediction of user interests and preferences according to contextual information...
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Study of Vehicle Dynamics Using Tensor Analysis
This paper highlights a vehicle’s dynamics study using elements from tensor calculus, considered as a superior step of the matrix calculus. The...
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Comparative Analysis of the Hierarchical 3D-SVD and Reduced Inverse Tensor Pyramid in Regard to Famous 3D Orthogonal Transforms
In this work are presented two new approaches for hierarchical decomposition represented as tensors of size N × N × N for N = 2n, based on algorithms...
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Top-N Recommendation System Using Explicit Feedback and Outer Product Based Residual CNN
Deep Neural Networks (DNN) has attained impressive results in various natural language processing tasks. It attracts the researchers to apply DNN in...
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Singularity-Free Extraction of a Dual Quaternion from Orthogonal Dual Tensor
The parameterization of a rigid-body motion can be done using multiple algebraic entities. A very important criterion when choosing a...
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A Light Weight Traffic Volume Prediction Approach Based on Finite Traffic Volume Data
As one of the key technologies of intelligent transportation systems, short-term traffic volume prediction plays an increasingly important role in...