Survey of Text Mining II

1. Clustering

1. Cluster-Preserving Dimension Reduction Methods for Document Classification
Peg Howland, Haesun Park

2. Automatic Discovery of SimilarWords
Pierre Senellart, Vincent D. Blondel

3. Principal Direction Divisive Partitioning with Kernels and k-Means Steering
Dimitrios Zeimpekis, Efstratios Gallopoulos

4. Hybrid Clustering with Divergences
Jacob Kogan, Charles Nicholas, Mike Wiacek

5. Text Clustering with Local Semantic Kernels
Loulwah AlSumait, Carlotta Domeniconi

2. Document Retrieval and Representation

6. Vector Space Models for Search and Cluster Mining
Mei Kobayashi, Masaki Aono

7. Applications of Semidefinite Programming in XML Document Classification
Zhonghang Xia, Guangming Xing, Houduo Qi, Qi Li

3. Email Surveillance and Filtering

8. Discussion Tracking in Enron Email Using PARAFAC
Brett W. Bader, Michael W. Berry, Murray Browne

9. Spam Filtering Based on Latent Semantic Indexing
Wilfried N. Gansterer, Andreas G. K. Janecek, Robert Neumayer

4. Anomaly Detection

10. A Probabilistic Model for Fast and Confident Categorization of Textual Documents
Cyril Goutte

11. Anomaly Detection Using Nonnegative Matrix Factorization
Edward G. Allan, Michael R. Horvath, Christopher V. Kopek, Brian T. Lamb, Thomas S. Whaples, Michael W. Berry

12. Document Representation and Quality of Text: An Analysis
Mostafa Keikha, Narjes Sharif Razavian, Farhad Oroumchian, Hassan Seyed Razi

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Avainsanat: COMPUTERS / Computer Science COM014000