Relevance Feature Search for Text Mining using FClustering Algorithm

Kamble, R. R.; Kodavade, D. V.

doi:10.26438/ijcse/v6i7.223227

Cited by 22 publications

(11 citation statements)

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“…Reference [4] proposed a calligraphic character retrieval method based on the similarity of calligraphic character outlines.…”

Section: Related Workmentioning

confidence: 99%

Feature Extraction and Identification of Calligraphy Style Based on Dual Channel Convolution Network

Ziyan

2022

Security and Communication Networks

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To improve the effect of calligraphy style feature extraction and identification, this study proposes a calligraphy style feature extraction and identification technology based on two-channel convolutional neural network and constructs an intelligent calligraphy style feature extraction and identification system. Moreover, this paper improves the C3D network model and retains 2 fully connected layers. In addition, by extracting the outline skeleton and stroke features of calligraphy characters, this paper calculates the feature weight and authenticity determination function and constructs an authenticity identification system. The experimental study shows that the calligraphy style feature extraction and identification system based on the dual-channel convolutional neural network proposed in this paper has a good performance in calligraphy style feature extraction and identification.

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“…Reference [4] proposed a calligraphic character retrieval method based on the similarity of calligraphic character outlines.…”

Section: Related Workmentioning

confidence: 99%

Feature Extraction and Identification of Calligraphy Style Based on Dual Channel Convolution Network

Ziyan

2022

Security and Communication Networks

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“…In comparison to statistical machine translation, neural machine translation uses an end-to-end model architecture and vectorizes the sentence to extract the semantic features and information of the sentence, resulting in a smoother translated translation that is more in line with the grammatical characteristics of the language and higher translation quality. erefore, the neural machine translation model has become the mainstream translation system [1].…”

Section: Introductionmentioning

confidence: 99%

Computational Application on English Translation System Based on Intelligent Image Text Recognition

Wang¹,

Li²

2022

Security and Communication Networks

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This work offers an enhanced intelligent picture text recognition algorithm based on the intelligent image text recognition method to increase the impact of English image text translation. Texture blocks of adaptable size are used to successfully increase the accuracy and efficiency of restoration due to the varying texture information present in various photos. Furthermore, the repair sequence is altered as a result of the improved priority calculation algorithm, and the weight of the structural information is enhanced at the same time. In addition, in order to reduce the overall structural complexity and calculation amount of the system, the gated loop unit is also selected as the RNN structure. Finally, this article constructs an English translation system based on intelligent image text recognition according to the requirements of intelligent image text recognition and designs experiments to evaluate the performance of the system constructed in this article. The experimental statistical results show that the English translation system constructed in this article can basically meet the needs of English image text recognition.

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“…With the increasing progress of natural language processing technology in the study of Chinese language, it can even gradually support the analysis of rhythm, emotional element, and style characteristics of classical poetry [2]. "Computational Poetics" is proposed in this context [3].…”

Section: Related Workmentioning

confidence: 99%

Analysis of Poetry Style Based on Text Classification Algorithm

Can

2022

Scientific Programming

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In order to realize the effect of intelligent poetry style analysis, this paper applies the text classification algorithm to the poetry style analysis, combines the knowledge representation algorithm to perform text classification and recognition, improves the algorithm, and applies it to the poetry style analysis model. Moreover, this paper combines intelligent algorithms to construct a poetry style analysis system, constructs the system’s functional modules, preprocesses the poetry documents in the corpus, and maps them to the vector space that can be directly processed by the computer. In addition, after constructing the system model, this paper verifies the poetry style analysis system based on the text classification algorithm through simulation experiments. From the research results, the effect of the poetry style analysis method based on the text classification algorithm proposed in this paper is very good, which meets the actual needs of poetry style analysis.

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Relevance Feature Search for Text Mining using FClustering Algorithm

Cited by 22 publications

References 0 publications

Feature Extraction and Identification of Calligraphy Style Based on Dual Channel Convolution Network

Feature Extraction and Identification of Calligraphy Style Based on Dual Channel Convolution Network

Computational Application on English Translation System Based on Intelligent Image Text Recognition

Analysis of Poetry Style Based on Text Classification Algorithm

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