Tensor Term Indexing: An application of HOSVD for Document Summarization
In this paper, a new method for text summarization is proposed by using an extended version of the Tensor Term Importance (TTI) model. This method summarizes documents by extracting important sentences from a document. It improves the per document summarization efficiency by incorporating additional information of the whole document set referring to the same topic (or coherent documents). The basic idea of this approach is to represent the whole document set in a uniform form, in the...[Show more]
|Collections||ANU Research Publications|
|Source:||Proceedings of the 4th International Symposium on Computational Intelligence Informatics (ISCII 2009)|
|01_Manna_Tensor_Term_Indexing:_An_2009.pdf||221.17 kB||Adobe PDF||Request a copy|
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