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The coupling framework of modern literary works and traditional culture is first discussed in this paper, and the intrinsic connection between them is examined. Secondly, a semantic-associated information extraction network model is constructed using LSTM and attention mechanism, and the target semantic fusion is achieved through semantic space con...
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Context 1
... addition, the creation of literary works is closely related to the inheritance and promotion of traditional culture, and different types of literary works reflect local customs and habits or deeper traditional cultural connotations. The creation of modern literary works and traditional culture are intrinsically linked, as shown in Figure 2. In a word, the progress and development of society can not be separated from the strong support of culture, and the essence of the excellent traditional culture deserves our in-depth study and inheritance because there exists a relationship of mutual integration, mutual promotion, and mutual supplementation between modern Chinese literary works and the excellent traditional culture. ...
Citations
... Su [22] have presented integrative improvement of modern LW with traditional culture combined by SAN modeling. Here, suggested a semantic space conversion with semantic-related information extraction were used to achieve target semantic fusion. ...
... The harmonic means of sensitivity, precision. It is computed by equation (22) recall ecision recall ecision Score F + = − Pr * Pr * 2 1 (22) B. Performance analysis ...
The development of foreign literature, embodiment of emotional value in modern, contemporary foreign literature is more attentive on experience, through reading it, one can understand humanistic, personal feelings embedded in the work and grasp the author’s personality, spiritual experience. To analyze sentiment data of foreign literary works, proposed Emotion Analysis of Literary Works Based on Qutrit-inspired Fully Self-supervised Quantum Neural Network Method (EA-LW- QIFSQN). Initially input data are collected from NLP-dataset. Afterward, the input data provided to preprocessing. In preprocessing segment Federated Neural Collaborative Filtering (FNCF) is used to clean the unwanted data. Then preprocessed data is fed to feature extraction, synchro spline-kernelled chirplet extracting transform (SKCET) is used to extract two features such as textual features and lexical features. Afterwards QIFSQN is used to classify the emotions likes joy, sadness, anger, fear. Generally, QIFSQN doesn’t show some optimization adaption techniques to determine optimum parameter to offer accurate detection. Polar Coordinate Bald Eagle Search Algorithm (PCBSOA) is proposed to enhance QICCN classifies the emotions accurately. The proposed technique is executed and efficacy of EA-LW- QIFSQN technique is assessed with support of numerous performances like accuracy, recall, precision and F1-scorce is analyzed. Then, performance of EA-LW- QIFSQN technique is analyzed with existing techniques like emotion analysis of literary works depend on attention mechanisms with fusion of two-channel features (EA-LW-CNN), integrative improvement of modern literary works with traditional culture combined by semantic association network modeling(EA-LW-SAN) and emotion expression in modern literary appreciation: emotion-depend analysis (EA-LW-RFA) respectively.
