Personalized recommendation of film and television culture based on an intelligent classification algorithm

Cong, Hongyan

doi:10.1007/s00779-019-01271-8

Cited by 21 publications

(9 citation statements)

References 22 publications

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“…In the later stage of PBL teaching, the teacher spent two class hours to complete it, mainly for each group to display the animation greeting card works of the group, the team leaders and teachers of each group to score the works, and the students give scores for their cooperative learning and learning attitude with the group members according to the corresponding evaluation criteria [10]. e specific process is shown in Table 12.…”

Section: Later Stage Of Pbl Teachingmentioning

confidence: 99%

Exploring the Application of Online Teaching Platform in the PBL Teaching Mode of Film and Television Courses for Teacher Trainees

Jian

Yuan

2022

Mobile Information Systems

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The aim of the study is to deeply study the effect of the PBL teaching mode in improving students’ problem-solving ability, learning interest and autonomous learning ability. This study takes the practice teaching of film and television courses for normal students as the research object, constructs a general network teaching platform based on B/s and PBL teaching mode, deeply investigates the teaching status of film and television production practice courses, and selects the experimental class and control board to test the PBL teaching mode. The test results show that 13 students in the experimental class have a general learning attitude, 12 students have a good learning attitude, 7 students have a good learning attitude, and 5 students have a very correct learning attitude. This shows that 24 students have a positive learning attitude in the PBL teaching mode, which shows that they are very interested in learning information technology courses. At the same time, it also verifies the feasibility of the PBL teaching mode. At the same time, on this basis, this study puts forward some suggestions for the optimization of PBL teaching design under the network teaching platform.

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Section: Later Stage Of Pbl Teachingmentioning

confidence: 99%

Exploring the Application of Online Teaching Platform in the PBL Teaching Mode of Film and Television Courses for Teacher Trainees

Jian

Yuan

2022

Mobile Information Systems

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“…BP neural network is a traditional feed-forward fully connected neural network, which sets the learning rate and loss function, and updates the weights and thresholds through the backward error propagation algorithm, and the activation function is usually an S-type function, which can effectively train the network, but the convergence rate is slow and there is a problem of local minima [25]. e RBF neural network only contains a three-layer network structure, and the activation function is generally Gaussian, which has the generalization ability that the BP neural network cannot, and the training accuracy is better than that of the BP neural network, but the accuracy of the test data prediction is not sufficient [26][27][28][29][30].…”

Section: Information Fusion Model Designmentioning

confidence: 99%

Wavelet Transform-Based 3D Landscape Design and Optimization for Digital Cities

Chen

Wang

Zhang

2022

International Journal of Antennas and Propagation

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As a hot concept, the digital city has developed rapidly in recent years. The digital city uses information technology to realize all the contents of the past, present, and future of the city on the network, and can build a three-dimensional visual landscape. However, the traditional information fusion model has the problems of noise susceptibility and low efficiency in landscape design. In order to solve the above problems, this article proposes a wavelet transform-based 3D landscape design and optimization method for digital cities, which removes the noise influenced by wavelet change and builds an information fusion model based on neural network to complete the design optimization of the three-dimensional landscape of the digital city. Firstly, for the wavelet change denoising problem, an effective denoising algorithm for natural noise and abnormal noise is proposed by combining convolutional neural network and wavelet transform. The algorithm extracts mixed feature information of local long path and local short path based on the information retention module, and decomposes the information by combining wavelet transform, inputs the different components obtained from the decomposition into the network for training, and removes the noise by subsequent feature screening of the network structure. Then, aiming at the optimization of 3D landscape design, an information fusion model based on long-short time memory network and radial basis backpropagation network is proposed for fusing multiple sources of information in the digital city to evaluate the landscape. The method collects digital city feature information at the information layer and preprocesses the feature information by a rate detection algorithm. Then, LSTM and RBF-BP neural networks in deep learning are used in the feature layer for adaptive learning of multiple feature signals, and finally, fuzzy logic is used to control the system decision output to improve the efficiency of 3D landscape design. Finally, the simulation experimental results show that the proposed denoising method in this article can better retain the texture details in the images and the denoised images have better visual effects; the proposed information fusion model has higher accuracy compared with the traditional methods. Combining this method to design and optimize 3D landscapes in digital cities can improve the efficiency of landscape design.

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“…The precision push technology in the new media app solves this problem. It first collects audience information with the help of big data technology, and then uses artificial intelligence technology to accurately predict the audience's cultural interests, analyze the audience's usage habits, and formulate personalized communication strategies, so as to realize the unification of supply and demand between pushing content and audience needs, and improve the accuracy and effectiveness of traditional culture communication [ 28 ]. Take Jiyin App as an example, it combines the use of big data algorithm and artificial autonomous selection technology to push traditional culture related to the elements of interest to the audience in a timely manner and promote the dissemination of traditional culture [ 29 ].…”

Section: Related Workmentioning

confidence: 99%

Exploring the Path of Innovative Development of Traditional Culture under Big Data

Li¹

2022

Computational Intelligence and Neuroscience

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Chinese traditional culture is the treasure of our cultural field. In the new era, it is of great significance to give traditional culture a new life and vitality. The term “big data” is hotly debated all over the world, while the development of big data is gradually occupying all aspects of the society that people are compatible with society. It is an imperative initiative to build a cultural data system by making use of big data technology, and cultural big data can make Chinese traditional culture release more vitality. This paper analyzes the new characteristics of traditional culture development from big data in helping traditional culture inheritance and innovation and proposes new ideas and creates more possibilities for the development of traditional culture. Combining with big data technology, this paper proposes an improvement to the data sparsity problem and cold-start problem of collaborative filtering recommendation algorithm and also improves the recommendation algorithm based on association rules. The association rule technique is used to compensate for the cold-start and data sparsity problems of new users often encountered by collaborative filtering techniques; the aim is to obtain recommendation results with high user satisfaction. Experiments on traditional cultural resource datasets show that the method in this paper effectively solves the data sparsity and cold-start problems that exist in traditional collaborative filtering techniques, and the recommendation accuracy surpasses that of other methods.

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Personalized recommendation of film and television culture based on an intelligent classification algorithm

Cited by 21 publications

References 22 publications

Exploring the Application of Online Teaching Platform in the PBL Teaching Mode of Film and Television Courses for Teacher Trainees

Exploring the Application of Online Teaching Platform in the PBL Teaching Mode of Film and Television Courses for Teacher Trainees

Wavelet Transform-Based 3D Landscape Design and Optimization for Digital Cities

Exploring the Path of Innovative Development of Traditional Culture under Big Data

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