Research on Music Content Recognition and Recommendation Technology Based on Deep Learning

Yang, Gao

doi:10.1155/2022/7696840

Cited by 9 publications

(7 citation statements)

References 26 publications

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“…Employees should have today's skills and performance capable of adaptation in a changing world and a complex social background [80]. Moreover, nowadays, deep-learning technique have been revealed to be the best practice if one wants to optimize recommender system models [81], [82], [83]. SWOT analysis results for previous studies are shown in…”

Section: Mpia Et Almentioning

confidence: 99%

Applying Data Mining in Graduates’ Employability

2023

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Envisaging an adequate IT/IS solution that can mitigate the employability problems is imperative because nowadays there is a high rate of unemployed graduates. Thus, the main goal of this systematic literature review (SLR) was to explore the application of data mining techniques in modeling employability and see how those techniques have been applied and which factors/variables have been retained to be the most predictors or/and prescribers of employability. Data mining techniques have shown the ability to serve as decision support tools in predicting and even prescribing employability. The review determined and analyzed the machine learning algorithms used in data mining to either predict or prescribe employability. This review used the PRISMA method to determine which studies from the existing literature to include as items for this SLR. Hence, 20 relevant studies, 16 of which are predicting employability and 4 of which are prescribing employability. These studies were selected from reliable databases: ScienceDirect, Springer, Wiley, IEEE Xplore, and Taylor and Francis. According to the results of this study, various data mining techniques can be used to predict and/or to prescribe employability. Furthermore, the variables/factors that predict and prescribe employability vary by country and the type of prediction or prescription conducted research. Nevertheless, all previous studies have relied more on skill as the main factor that predict and/or prescribe employability in developed countries and none studies have been conducted in unstable developing countries. Therefore, the need to conduct research on predicting or prescribing employability in such countries by trying to use contextual factors beyond skill as features.

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Section: Mpia Et Almentioning

confidence: 99%

Applying Data Mining in Graduates’ Employability

2023

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“…Recent music recommendation systems utilize deep learning in order to identify musical content [16]. Raju et al utilize a hybrid network using a CNN and an LSTM module for music genre classification [13].…”

Section: Related Workmentioning

confidence: 99%

Music Recommendations Based on User's Mood Using Convolutional Neural Networks

Petrescu¹

2022

Studia UBB Informatica

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"This paper proposes a method for music recommendations using emotions, using deep learning techniques. The method is composed of two modules. The emotion detection module, which utilizes a hybrid architecture involving a Convolutional Neural Network (CNN) and a Reccurent Neural Network using Long-Short Term Memory (LSTM) Cells. We compared individual architectures of CNNs and LSTMs against our hybrid approach, outperforming them during experiments. We evaluated the modules on our own data set, created using Spotify’s API and containing 2028 songs from different genres and linguistic families, labeled with valence and arousal values. The model also outperforms other related approaches, however we did not evaluate them on the same data set. The predictions are used by the second module, for which we proposed a simple method of ordering the results based on the similarity to user’s input. Keywords and phrases: mood, emotion, valence, energy, convolutional neural network, recurrent neural networks, long-short term memory, hybrid, regression, classification. "

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“…Recommendation Technology Based on Deep Learning" [1] due to concerns that the peer review process has been compromised.…”

Section: Security and Communication Network Has Retracted The Article...mentioning

confidence: 99%

Retracted: Research on Music Content Recognition and Recommendation Technology Based on Deep Learning

Networks¹

2022

Security and Communication Networks

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Research on Music Content Recognition and Recommendation Technology Based on Deep Learning

Cited by 9 publications

References 26 publications

Applying Data Mining in Graduates’ Employability

Applying Data Mining in Graduates’ Employability

Music Recommendations Based on User's Mood Using Convolutional Neural Networks

Retracted: Research on Music Content Recognition and Recommendation Technology Based on Deep Learning

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