کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
416599 681388 2007 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Updating the partial singular value decomposition in latent semantic indexing
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر نظریه محاسباتی و ریاضیات
پیش نمایش صفحه اول مقاله
Updating the partial singular value decomposition in latent semantic indexing
چکیده انگلیسی

Latent semantic indexing (LSI) is a method of information retrieval (IR) that relies heavily on the partial singular value decomposition (PSVD) of the term-document matrix representation of a data set. Calculating the PSVD of large term-document matrices is computationally expensive; hence in the case where terms or documents are merely added to an existing data set, it is extremely beneficial to update the previously calculated PSVD to reflect the changes. It is shown how updating can be used in LSI to significantly reduce the computational cost of finding the PSVD without significantly impacting performance. Moreover, it is shown how the computational cost can be reduced further, again without impacting performance, through a combination of updating and folding-in.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Computational Statistics & Data Analysis - Volume 52, Issue 1, 15 September 2007, Pages 174–183
نویسندگان
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