潜在的意味を用いた情報フィルタリング Information Filtering Using Latent Semantics
We propose an information filtering system using latent semantics obtained by the Singular Value Decomposition(SVD) and the Independent Component Analysis(ICA). Document vectors usually have too many elements. So we are obliged to spend much time to apply the ICA for the document vectors. To solve this problem, the present method combines the SVD which is often used for decreasing dimension and the ICA. Before applying the ICA, we represent documents with singular vectors obtained by the SVD. We measure processing times to carry out the ICA without the SVD and the proposed method for comparison of these methods. In addition, we construct a user profile in space consisted of latent semantics obtained by the present method, and discuss accuracy of recommendation.
- 電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society
電気学会論文誌. C, 電子・情報・システム部門誌 = The transactions of the Institute of Electrical Engineers of Japan. C, A publication of Electronics, Information and System Society 126(7), 865-870, 2006-07-01
The Institute of Electrical Engineers of Japan