頁籤選單縮合
題名 | An Experimental Study of Incremental SVD on Latent Semantic Analysis |
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作 者 | Shen, Bo; Zhao, Ying-si; | 書刊名 | Journal of Internet Technology |
卷期 | 15:1 2014.01[民103.01] |
頁次 | 頁35-41 |
分類號 | 312.1 |
關鍵詞 | Internet; Singular value decomposition; Latent semantic analysis; Experiment; Incremental SVD; |
語文 | 英文(English) |
英文摘要 | Singular value decomposition is an important method to factorize a matrix, which is useful for many applications, such as principal component analysis in statistics and latent semantic analysis in natural language text processing. In order to diminish the computational complexity, incremental update algorithm is developed, especially for analyzing relationships between text documents. However, it is at the cost of a reduction in precision. In this paper, we study the effect of incremental update on latent semantic analysis; and, by experiments, to investigate the trend downward of computing precision and then try to find the balance point between re-computation and incremental update. The results indicate that when increased documents are less than original documents, incremental update method has an approximate precision to re-computing method, and then its recall ratio will obviously decline. It could be helpful for deciding when the matrix factorization must be recomputed. |
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