TY  - GEN
AU  - Rubin, Timothy N.
AU  - Chambers, America
AU  - Smyth, Padhraic
AU  - Steyvers, Mark
A2  - 
T1  - Statistical Topic Models for Multi-Label Document Classification
JO  - 
PB  - 
C1  - 
PY  - 2011/
VL  - 
IS  - 
SP  - 
EP  - 
UR  - http://arxiv.org/abs/1107.2462
DO  - 
KW  - mining
KW  - model
KW  - text
KW  - tm
KW  - topic
KW  - toread
L1  - 
N1  - Statistical Topic Models for Multi-Label Document Classification
N1  - 
AB  -   Machine learning approaches to multi-label document classification have (to date) largely relied on discriminative modeling techniques such as support vector machines. A drawback of these approaches is that performance rapidly drops off as the total number of labels and the number of labels per document increase. This problem is amplified when the label frequencies exhibit the type of highly skewed distributions that are often observed in real-world datasets. In this paper we investigate a class of generative statistical topic models for multi-label documents that associate individual word tokens with different labels. We investigate the advantages of this approach relative to discriminative models, particularly with respect to classification problems involving large numbers of relatively rare labels. We compare the performance of generative and discriminative approaches on document labeling tasks ranging from datasets with several thousand labels to datasets with tens of labels. The experimental results indicate that generative models can achieve competitive multi-label classification performance compared to discriminative methods, and have advantages for datasets with many labels and skewed label frequencies. 
ER  -

TY  - JOUR
AU  - Carpena, P.
AU  - Bernaola-Galván, P.
AU  - Hackenberg, M.
AU  - Coronado, A. V.
AU  - Oliver, J. L.
T1  - Level statistics of words: Finding keywords in literary texts and symbolic sequences
JO  - Physical Review E (Statistical, Nonlinear, and Soft Matter Physics)
PY  - 2009/
VL  - 79
IS  - 3
SP  - 
EP  - 
UR  - http://bioinfo2.ugr.es/TextKeywords/
DO  - 10.1103/PhysRevE.79.035102
KW  - analysis
KW  - extraction
KW  - keyword
KW  - statistical
KW  - text
KW  - tm
KW  - topic
KW  - toread
L1  - 
SN  - 
N1  - Level statistics of words: Finding keywords in literary texts and symbolic sequences
N1  - 
AB  - 
ER  -