Abstract
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.
Contact author: Charles Nicholas, Department of Computer Science and Electrical Engineering, UMBC, 1000 Hilltop Circle, Baltimore, MD 21250 USA, 410-455-2594, -3969 (fax), nicholas@cs.umbc.edu
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© 1998 Springer-Verlag Berlin Heidelberg
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Nicholas, C., Dahlberg, R. (1998). Spotting Topics with the Singular Value Decomposition. In: Munson, E.V., Nicholas, C., Wood, D. (eds) Principles of Digital Document Processing. PODDP 1998. Lecture Notes in Computer Science, vol 1481. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-49654-8_7
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DOI: https://doi.org/10.1007/3-540-49654-8_7
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