An Advanced Fuzzy Constructing Algorithm for Feature Discovery in Text Mining

Ramalakshmi, E.; Golla, Subhakar

doi:10.5120/ijca2015906720

Cited by 16 publications

(6 citation statements)

References 14 publications

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“…Reference [7] proposes a SC.HoG feature to describe calligraphy characters, which expresses the position information of a certain contour point of calligraphy characters and the distribution information of contour points around the contour point, so as to perform shape-based retrieval for calligraphy characters. Reference [8] first performs pruning processing, and filters out calligraphic character images that are impossible to be similar to the calligraphic character image to be retrieved by comparing the complexity of calligraphy characters, stroke density, and other characteristics. Dimensional calligraphy image feature data is used for retrieval, and PK-tree is used to improve retrieval speed.…”

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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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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“…Ramalakshmi & Golla proposed a document search model based on fuzzy logic, called Fuzzy Relevance Feature Discovery Algorithm (FRFDA), In addition to performing similarity comparisons on the features of different levels of word patterns, and updating the correlation and distribution of the weights of these words after classifying the words [19],…”

Section: A Fuzzy Techniques In Statistical Methodsmentioning

confidence: 99%

Review of Survey Research in Fuzzy Approach for Text Mining

Lai

Chen

2023

IEEE Access

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Text mining has been common research field, with the emergence of Web 2.0 and the development of social software, the amount of text generated every day has increased dramatically. The texts contain a lot of valuable information, how to analysis for the information from text is very important. Therefore, many research have explored related methods and various fields of text mining, such as sentiment analysis, text clustering, text summarization, etc., However, unlike other numerical data that can be directly calculated in terms of character performance, the calculation must be performed after vector conversion, and the words may have polysemy, which provides more challenges for natural language processing. Due to the above challenges, various techniques are used for data preprocessing before analysis. In addition to the common statistical and discrete methods for text data, methods based on fuzzy logic provide another option for effective natural language analysis, Therefore, in recent years, more and more studies have added Fuzzy logic to additionally capture the context semantics of individual words to help more accurate natural language processing. This survey research discusses multiple text mining methods, The survey paper discusses multiple text mining methods, subfields and application fields, covering the literature published between 2010 and 2022, It is organized to the subtasks to be performed, the methods and natural language processing techniques used, and the application scenarios. At the end of this study, the research has provided the key point discussion and relevant suggestions for text mining combined with fuzzy logic.

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“…The literature [8] proposed a blind deblurring algorithm combining variational Bayesian and adaptive sparse prior learning. The literature [9] summarized the methods of blind defuzzification based on this kind of theory in recent years. Because the theoretical derivation of this kind of work is difficult and the calculation is complicated, the attention has been low.…”

Section: Related Workmentioning

confidence: 99%

Intelligent recognition of English fuzzy text and teaching based on parallel projection and region expansion

Wang

2023

Preprint

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The most important and difficult point of English fuzzy text is how to effectively improve boundary segmentation and character classification. Traditional fuzzy text recognition models are often difficult to accurately identify the characteristics of fuzzy English text. In order to improve the effect of English fuzzy text recognition, based on machine learning technology, this paper combines parallel projection and region expansion technology to construct an English fuzzy text intelligent recognition system. Moreover, based on the idea of region growth, this paper expands the triangular facets of the same processing area onto the same plane, then recalculates the associated texture points, and uses the rotation and translation method to wrap the two-dimensional vector texture on the surface of the three-dimensional model, which effectively solves the problem of entanglement of the two-dimensional vector map on the three-dimensional model when the texture information is insufficient, and realizes the intelligent recognition of fuzzy English characters with the support of the intelligent database. In addition, this paper designs a controlled experiment to analyze the recognition effect. The research results show that the model constructed in this paper works well.

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An Advanced Fuzzy Constructing Algorithm for Feature Discovery in Text Mining

Cited by 16 publications

References 14 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

Review of Survey Research in Fuzzy Approach for Text Mining

Intelligent recognition of English fuzzy text and teaching based on parallel projection and region expansion

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