| Latent
Semantic Indexing |
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| • | Like
vector model, use document-term matrix. |
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| • | Apply
singular value decomposition (SVD) to |
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| produce
a set of ranked eigenvalues. These |
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| represent
abstract concepts in the document |
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| space. |
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| • | Select
the top eigenvalues (e.g., first 200) and |
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| apply
to query-document matching (See Efron |
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| dissertation) |
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| • | Retrieves
some documents that may not use the |
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| query
term |
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