A short text feature extension algorithm based on improved frequent word set is proposed. By calculating support and confidence, the same category tendencies of frequent term sets are extracted. Correlations based frequent term sets are defined to further extend the term set. Meanwhile, information gain is introduced to traditional TF-IDF, better expressing the category distribution information and the weight of word for each category is enhanced. All term pairs with external relations are extracted and the frequent term set is expanded. Finally, the word similarity matrix is constructed via the frequent word set, and the symmetric non-negative matrix factorization technique is applied to extend the feature space. Experiments show that the constructed short text model can improve the performance of short text clustering.
Wireless virtual reality integrated multidisciplinary technology, combined with related industries and fields, has changed the way of human-computer interaction and opened up a new field of user experience. In recent years, with the rapid improvement of computer technology and hardware conditions, interactive technology has developed rapidly. The existing wireless virtual reality interactive system is too single and cannot be used in multiple environments. The original system requires a large number of sensor equipment, the cost is high, and the traditional perception technology is too restrictive and cannot realize human-computer interaction more naturally. This paper proposes a dual intention perception algorithm based on the fusion of touch (obtained by experimental simulation equipment), hearing, and vision. The algorithm can perceive the user’s operation intention through the user’s natural behavior and can identify the user’s two intentions at the same time. This paper proposes a navigational interactive mode, which provides users with multimodal intelligent navigation through intelligent perception of user intent and experimental progress. We determine the impact model of the interactive system effect evaluation and analyze its effect evaluation strategy in depth and then further quantify the indicators under the four effect dimensions of information perception, artistic reflection, social entertainment, and aesthetic experience. A combination of qualitative and quantitative methods was used to carry out relevant research on effect evaluation, usability test, and questionnaire interview. The experimental results show that this interactive system has better entertainment effects than other forms of film and television animation, but still needs to pay attention to and strengthen the construction and embodiment of film and television animation content, as well as the optimization and perfection of the fault-tolerant mechanism in the design process.
The development of 3D modeling technology has promoted the development of the multimedia film and television industry. This article is aimed at studying the design of 3D modeling facial image library in multimedia film and television, at providing a more comprehensive facial image library for the multimedia film and television industry, at breaking the shackles of the traditional film and television industry with 3D technology, and at continuously surpassing traditional film and television media forms. This article deeply explores the background development of multimedia film and television and the characteristics of the development of new media. Starting from 3D technology, it extracts facial features of characters, transforms image data through deep autoencoders, and uses local binarization mode to perform the original facial image is subjected to texture feature extraction. In this paper, a number of experimental subjects were selected, and the subjects were photographed from the left, front, and right from multiple angles. Through the pinhole camera projection imaging process, the internal and external parameters of the camera were adjusted. In the process of 3D image construction, the image is first selected for feature detection, then the corresponding vector information and geometric conditions are matched to construct a 3D matrix, and the facial structure image is obtained by triangulation. This article compares the 3D production software on the market and selects the Maya platform suitable for building this system. The global constraint information is obtained by training some sample images. When searching the test image, find the appropriate feature point position according to the structural matching degree of the local image. When each search is completed, the global information will be used for constraint, so as to output reasonable feature information. The average residual range of the human face image constructed in this paper is 0.25-0.45, and the maximum residual error does not exceed 4.0. The experimental method in this paper has good stability and robustness. Using the COM transmission model can make experimenters not need to think too much about the underlying details. This face animation-driven simulation scheme can achieve more vivid facial expressions.
Background: De novo peptide sequencing is one of the key technologies in proteomics, which can extract peptide sequences directly from tandem mass spectrometry (MS/MS) spectra without any protein databases. Since the accuracy and efficiency of de novo peptide sequencing can be affected by the quality of the MS/MS data, the DeepNovo method using deep learning for de novo peptide sequencing is introduced, which outperforms the other state-of-the-art de novo sequencing methods. Objective: For superior performance and better generalization ability, additional ion types of spectra should be considered and the model of DeepNovo should be adaptive. Method: Two improvements are introduced in the DeepNovo A+ method: a_ions are added in the spectra analysis, and the validation set is used to automatically determine the number of training epochs. Results: Experiments show that compared to the DeepNovo method, the DeepNovo A+ method can consistently improve the accuracy of de novo sequencing under different conditions. Conclusion: By adding a_ions and using the validation set, the performance of de novo sequencing can be improved effectively.
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