Unsupervised document classification using sequential information maximization

Authors: Noam Slonim, Nir Friedman Naftali Tishby

Contributors: The Pennsylvania State University CiteSeerX Archives

Source: http://www.cs.rutgers.edu/~mlittman/topics/dimred02/slonim.pdf.

Subject Terms: I.5.3 [Pattern Recognition, Clustering—Algorithms, I.5.4 [Pattern Recognition, Applications—Text processing, E.4 [Data, Coding and Information Theory—Data compaction and compression General Terms Algorithms, Theory, Performance, Experimentation

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.85.3622; http://www.cs.rutgers.edu/~mlittman/topics/dimred02/slonim.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.85.3622
http://www.cs.rutgers.edu/~mlittman/topics/dimred02/slonim.pdf

Unsupervised document classification using sequential information maximization

Authors: Noam Slonim, Nir Friedman Naftali Tishby

Contributors: The Pennsylvania State University CiteSeerX Archives

Source: http://www.cs.huji.ac.il/~nirf/Papers/SFT2.pdf.

Subject Terms: I.5.3 [Pattern Recognition, Clustering—Algorithms, I.5.4 [Pattern Recognition, Applications—Text processing, E.4 [Data, Coding and Information Theory—Data compaction and compression General Terms Algorithms, Theory, Performance, Experimentation

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.81.967; http://www.cs.huji.ac.il/~nirf/Papers/SFT2.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.81.967
http://www.cs.huji.ac.il/~nirf/Papers/SFT2.pdf

Unsupervised document classification using sequential information maximization

Authors: Noam Slonim, Nir Friedman Naftali Tishby

Contributors: The Pennsylvania State University CiteSeerX Archives

Source: http://www.cs.huji.ac.il/~nir/Papers/SFT2.ps.

Subject Terms: I.5.3 [Pattern Recognition, Clustering—Algorithms, I.5.4 [Pattern Recognition, Applications—Text processing, E.4 [Data, Coding and Information Theory—Data compaction and compression General Terms Algorithms, Theory, Performance, Experimentation

File Description: application/postscript

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.3723; http://www.cs.huji.ac.il/~nir/Papers/SFT2.ps

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.80.3723
http://www.cs.huji.ac.il/~nir/Papers/SFT2.ps

Unsupervised document classification using sequential information maximization

Authors: Noam Slonim, Nir Friedman Naftali Tishby

Contributors: The Pennsylvania State University CiteSeerX Archives

Source: http://www.princeton.edu/~nslonim/publications/SIGIR2002.pdf.

Subject Terms: I.5.3 [Pattern Recognition, Clustering—Algorithms, I.5.4 [Pattern Recognition, Applications—Text processing, E.4 [Data, Coding and Information Theory—Data compaction and compression General Terms Algorithms, Theory, Performance, Experimentation

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.5598; http://www.princeton.edu/~nslonim/publications/SIGIR2002.pdf

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.124.5598
http://www.princeton.edu/~nslonim/publications/SIGIR2002.pdf

Unsupervised document classification using sequential information maximization

Authors: Noam Slonim, Nir Friedman Naftali Tishby

Contributors: The Pennsylvania State University CiteSeerX Archives

Source: http://www.cis.uab.edu/zhang/Spam-mining-papers/Unsupervised.Document.Classification.using.Sequential.Information.Maximization.pdf.

Subject Terms: Categories and Subject Descriptors I.5.3 [Pattern Recognition, Clustering—Algorithms, I.5.4 [Pattern Recognition, Applications—Text processing, E.4 [Data, Coding and Information Theory—Data compaction and compression General Terms Algorithms, Theory, Performance, Experimentation

File Description: application/pdf

Relation: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.408.6254

Availability: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.408.6254
http://www.cis.uab.edu/zhang/Spam-mining-papers/Unsupervised.Document.Classification.using.Sequential.Information.Maximization.pdf