Latent semantic analysis (LSA), as one of the most popular unsupervised dimension reduction tools, has a wide range of applications in text mining and information retrieval. The k...
Xi Chen, Yanjun Qi, Bing Bai, Qihang Lin, Jaime G....
Sensory systems often use groups of redundant neurons to represent stimulus information both during transduction and population coding of features. This redundancy makes the syste...
Most text mining methods are based on representing documents using a vector space model, commonly known as a bag of word model, where each document is modeled as a linear vector r...
Rowena Chau, Ah Chung Tsoi, Markus Hagenbuchner, V...
Document classification presents difficult challenges due to the sparsity and the high dimensionality of text data, and to the complex semantics of the natural language. The tradi...
The problem of document classification considers categorizing or grouping of various document types. Each document can be represented as a bag of words, which has no straightforw...