document: Variable latent semantic indexing Latent Semantic Indexing is a classical method to produce optimal low-rank approximations of a term-document matrix . However , in the context of a particular query distribution , the approximation thus produced need not be optimal . We propose VLSI , a new query-dependent ( or `` variable '' ) low-rank approximation that minimizes approximation error for any specified query distribution . With this tool , it is possible to tailor the LSI technique to particular settings , often resulting in vastly improved approximations at much lower dimensionality . We validate this method via a series of experiments on classical corpora , showing that VLSI typically performs similarly to LSI with an order of magnitude fewer dimensions .
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