Efficient text feature extraction by integrating the average linkage and K-medoids clustering
D Sun - Modern Physics Letters B, 2021 - World Scientific
By clustering feature words, we can not only simplify the dimension of feature subsets, but
also eliminate the redundancy of the feature. However, for a feature set with very large …
also eliminate the redundancy of the feature. However, for a feature set with very large …
A clustering based feature selection method using feature information distance for text data
S Chao, J Cai, S Yang, S Wang - … , ICIC 2016, Lanzhou, China, August 2-5 …, 2016 - Springer
Feature selection is a key point in text classification. In this paper a new feature selection
method based on feature clustering using information distance is put forward. This method …
method based on feature clustering using information distance is put forward. This method …
Chinese text clustering algorithm based k-means
M Yao, D Pi, X Cong - Physics Procedia, 2012 - Elsevier
Text clustering is an important means and method in text mining. The process of Chinese
text clustering based on k-means was emphasized, we found that new center of a cluster …
text clustering based on k-means was emphasized, we found that new center of a cluster …
Improved KNN algorithm applied term feature combination technology for Chinese textual classification
A feature combination method was presented to improve the KNN algorithm. Each term's
CHI value was calculated. Multiple discriminating words with same contribution on …
CHI value was calculated. Multiple discriminating words with same contribution on …
[PDF][PDF] A feature selection method based on concept extraction and SOM text clustering analysis
L Wang, M Jiang, S Liao, Y Lu - International Journal of Computer …, 2006 - researchgate.net
The feature selection is an important part in automatic classification. In this paper, we use
the HowNet to extract the concept attributes from word to build a feature set. However, as the …
the HowNet to extract the concept attributes from word to build a feature set. However, as the …
A text category detection and information extraction algorithm with deep learning
X Wu, Z Wu, Y Feng - Journal of Physics: Conference Series, 2021 - iopscience.iop.org
In order to solve the problem that the text classification model based on neural network is
easy to over-fit and ignore the key words in sentences in the training process, a Bi-GRU …
easy to over-fit and ignore the key words in sentences in the training process, a Bi-GRU …
Study on the Application of Complex Network Theory in Chinese Text Feature Selection
Z Hui, L Huailiang, F Yunjie - Data Analysis and …, 2012 - manu44.magtech.com.cn
This paper proposes a feature selection method based on complex network. The weighted
complex network of text is built to represent the semantic relations between words and text …
complex network of text is built to represent the semantic relations between words and text …
Research on text representation method based on improved TF-IDF
Y Fu, Y Yu - Journal of Physics: Conference Series, 2020 - iopscience.iop.org
According to the different importance degree between feature and text, this paper proposes
a method of improved traditional TF-IDF algorithm according to the position information of …
a method of improved traditional TF-IDF algorithm according to the position information of …