The singular value decomposition, or SVD, has been studied in the past as a tool for detecting and understanding patterns in a collection of documents. We show how the matrices produced by the SVD calculation can be interpreted, allowing us to spot patterns of characters that indicate particular topics in a corpus. A test collection, consisting of two days of AP newswire traffic, is used as a running example.
CITATION STYLE
Nicholas, C., & Dahlberg, R. (1998). Spotting topics with the singular value decomposition. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1481, pp. 82–91). Springer Verlag. https://doi.org/10.1007/3-540-49654-8_7
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