Significant term extraction by Higher Order SVD
In this paper, we present a novel method for term importance, called Tensor Term Indexing (TTI). This extracts significant terms from a document as well as a coherent collection of document set. The basic idea of this approach is to represent the whole document collection in a Term-Sentence-Document tensor and employs higher-order singular value decomposition (HOSVD) for important term extraction. TTI uses the lower rank approximation technique to reduce noise by eliminating anecdotal terms, to...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 7th International Symposium on Applied Machine Intelligence and Informatics Proceedings|
|01_Manna_Significant_term_extraction_by_2009.pdf||120.77 kB||Adobe PDF||Request a copy|
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