Patent Document ID: 8612369
Application ID: 13083402

Base Claim:
1. A computer-implemented method to apply a query to a set of documents, comprising: by a computer: reconstructing a document term matrix XεR N×M where N is a number of documents and M is a number of words, by minimizing reconstruction errors with min ∥X−UA∥, where A is a fixed projection matrix and U is a column orthogonal matrix; determining a loss function and parameter gradients to generate U; fixing U while determining the loss function and sparse regularization constraints on the projection matrix A; generating parameter coefficients and generating a sparse projection matrix A; and generating a Sparse Latent Semantic Analysis (Sparse SLA) model and applying the model to a set of documents and displaying documents matching a query.

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Claim 5:
5. The method of claim 1 , comprising adding an entry-wise l 1 -norm of A as a regularization term to the loss function and formulating the Sparse LSA model as: min U , A ⁢ 1 2 ⁢  X - UA  F 2 + λ ⁢  A  1 subject ⁢ - ⁢ to ⁢ : ⁢ ⁢ U T ⁢ U = I , where  A  1 = ∑ d = 1 D ⁢ ⁢ ∑ j = 1 M ⁢  a dj  is the entry-wise l 1 -norm of A and λ is a regularization parameter for a density (the number of nonzero entries) of A.