DocumentCode :
2865681
Title :
Text classification with evolving label-sets
Author :
Godbole, Shantanu ; Ramakrishnan, Ganesh ; Sarawagi, Sunita
Author_Institution :
IIT Bombay, India
fYear :
2005
fDate :
27-30 Nov. 2005
Abstract :
We introduce the evolving label-set problem encountered in building real-world text classification systems. This problem arises when a text classification system trained on a label-set encounters documents of unseen classes at deployment time. We design a class-detector module that monitors unlabeled data, detects new classes, and suggests them to the administrator for inclusion in the label-set. We propose abstractions that group together tokens under human understandable concepts and provide a mechanism of assigning importance to unseen terms. We present generative algorithms leveraging the notion of support of documents in a model for (1) selecting documents of proposed new classes, and (2) automatically triggering detection of new classes. Experiments on three real world taxonomies show that our methods select new class documents with high precision, and trigger emergence of new classes with low false-positive and false-negative rates.
Keywords :
classification; text analysis; class-detector module; document selection; evolving label-sets; generative algorithm; text classification; Algorithm design and analysis; Australia; Buildings; Constitution; Data mining; Error analysis; Humans; Robustness; Taxonomy; Text categorization;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Data Mining, Fifth IEEE International Conference on
ISSN :
1550-4786
Print_ISBN :
0-7695-2278-5
Type :
conf
DOI :
10.1109/ICDM.2005.143
Filename :
1565743
Link To Document :
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