Sequential Latent Semantic Indexing
Thus, this work offeres a sequential version of the LSI algorithm
(SLSI). Its main difference from the existing algorithms is that the
dimension of space is not fixed and dynamically changes to
ensure a given level of relative approximation error of a matrix of
observations. Experiments with a real text collections show that
the SLSI algorithm can be seen as a compromise, which has a
lower computational complexity and memory requirements
compared to the standard LSI method and does not lead to a
decrease of quality of classification in contrast to other sequential
algorithms.
Cite As
Vital (2024). Sequential Latent Semantic Indexing (https://www.mathworks.com/matlabcentral/fileexchange/22795-sequential-latent-semantic-indexing), MATLAB Central File Exchange. Retrieved .
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- AI, Data Science, and Statistics > Statistics and Machine Learning Toolbox > Dimensionality Reduction and Feature Extraction >
- AI, Data Science, and Statistics > Text Analytics Toolbox >
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TCSLSI/
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1.0.0.0 |