THE USE OF SINGULAR VALUE DECOMPOSITION (SVD) ON LATENT SEMANTIC INDEXING (LSI) FOR INFORMATION RETRIEVAL
Lately the approach to get a subject on written form from science data base depend on the match between words which used by user and the words which placed in the data base. It causes the variety of words which used to describe the same document. By using Singular Value Decomposition, which is deter...
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| 格式: | Theses |
| 語言: | Indonesia |
| 在線閱讀: | https://digilib.itb.ac.id/gdl/view/12082 |
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| 總結: | Lately the approach to get a subject on written form from science data base depend on the match between words which used by user and the words which placed in the data base. It causes the variety of words which used to describe the same document. By using Singular Value Decomposition, which is determine SVD from matrix term generally with referred document, there is an advantage in obtaining information from hidden document. The terms and the documents are represented by singular vector which subsequently matched with the user words. The retrieval method is called latent semantic indexing (LSI). By LSI the important connection between terms and documents are acquired. LSI is a method that widely could be applied, and could increase the access of the user to the information which is in written forms or documents or services which provide a describe on text. |
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