Latent Semantic Indexing
نویسندگان
چکیده
In the previous lecture, we discussed the Singular Value Decomposition (SVD) of the term-document matrix D ∈ <m× n where n is the number of documents in the corpus and m is the number of terms in the vocabulary. With the help of SVD (which is unique up to sign if the singular values are distinct), we can decompose an m×n term-document matrix into three special smaller matrices. The result is frequently abbreviated D = UΣV T where:
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تاریخ انتشار 2007