Showing posts with label dimensionality-reduction. Show all posts
Showing posts with label dimensionality-reduction. Show all posts
A novel approach for dimension reduction using word embedding: An enhanced text classification approach
*** Abstract: One of the challenging tasks in text classification is to reduce the dimensional feature space. This paper discusses an enhan...
High-Dimensional Text Clustering by Dimensionality Reduction and Improved Density Peak
*** Abstract: This study focuses on high-dimensional text data clustering, given the inability of K-means to process high-dimensional data a...
Ten quick tips for effective dimensionality reduction
*** Dimensionality reduction (DR) is frequently applied during the analysis of high-dimensional data. Both a means of denoising and simplif...
Textual data dimensionality reduction - a deep learning approach
*** Abstract: The growth of Internet has produced a high volume of natural language textual data. Such data can be sparse and may contain u...
Dimensionality Reduction and Clustering
*** In the previous post, we have looked at how to calculate the similarity of the document pairs using ‘Cosine Similarity’ algorithm and fo...
Text Data Pre-processing and Dimensionality Reduction Techniques for Document Clustering
*** `Abstract: Text mining refers generally to the process of extracting generally to the process of extracting interesting and non-trivial ...
Dimensionality Reduction for Text using Domain Knowledge
*** Abstract Text documents are complex high dimensional objects. To effectively visualize such data it is important to reduce its dimension...
Enhancing Text Analysis via Dimensionality Reduction
*** Abstract: Many applications require analyzing vast amounts of textual data, but the size and inherent noise of such data can make proces...
Exploration of dimensionality reduction for text visualization
*** Abstract: In the text document visualization community, statistical analysis tools (e.g., principal component analysis and multidimensio...
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