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Best Approximate of Vector Space Model by Using SVD | ||
| Al-Mustansiriyah Journal of Science | ||
| Article 1, Volume 28, Issue 2, 2017, Pages 133-139 | ||
| Author | ||
| Raghad M. Hadi | ||
| Abstract | ||
| A quick growth of internet technology makes it easy to assemble a huge volume of data as text document; e. g., journals, blogs, network pages, articles, email letters. In text mining application, increasing text space of datasets represent excessive task which makes it hard to pre-processing documents in efficient way to prepare it for text mining application like document clustering. The proposed system focuses on pre-processing document and reduction document space technique to prepare it for clustering technique. The mutual method for text mining problematic is vector space model (VSM), each term represent a features. Thus the proposed system create vector-space model by using pre-processing method to reduce of trivial data from dataset. While the hug dimensionality of VSM is resolved by using low-rank SVD. Experiment results show that the proposed system give better document representation results about 10% from previous approach to prepare it for document clustering. | ||
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