Getting More from the Singular Value Decomposition (SVD): Enhance Your Models with Document, Sentence, and Term Representations

Since its inception, SAS® Text Miner has used the singular value decomposition (SVD) to convert a termdocument matrix to a representation that is crucial for building successful supervised and unsupervised models. In this presentation, using SAS® code and SAS Text Miner, we compare these models with those that are based on SVD representations of subcomponents of documents. These more granular SVD representations are also used to provide further insights into the collection. Examples featuring visualizations, discovery of term collocations, and near-duplicate subdocument detection are shown.