See this document in CiteSeerX!

A New Pairwise Ensemble Approach  (Make Corrections)  
for Text Classification Yan Liu, Jaime Carbonell, Rong Jin School of Computer ...



  Home/Search   Context   Related

 
View or download:
cmu.edu/~yanliu/papers/ecml03.pdf
Cached:  PDF   PS.gz  PS  Image  Update  Help

From:  cmu.edu/~yanliu/research (more)
(Enter author homepages)

Rate this article: (best)
  Comment on this article  
(Enter summary)

Abstract: Text classification, whether by topic or genre, is an important task that contributes to text extraction, retrieval, summarization and question answering. In this paper we present a new pairwise ensemble approach, which uses pairwise Support Vector Machine (SVM) classifiers as base classifiers and "input-dependent latent variable" method for model combination. This new approach better captures the characteristics of genre classification, including its heterogeneous nature. Our... (Update)

Active bibliography (related documents):   More   All
0.2:   User Interfaces for Speech-Based Retrieval of Lecture Recordings - Hürst (2004)   (Correct)
0.0:   Generating Natural Language Summaries from Multiple On-Line.. - Radev (1999)   (Correct)
0.0:   UMASS Approaches to Detection and Tracking at TDT2 - Ron Papka James (1999)   (Correct)

Similar documents based on text:
0.0:   Unknown -   (Correct)

BibTeX entry:   (Update)

@misc{ classification-new,
  author = "For Text Classification",
  title = "A New Pairwise Ensemble Approach",
  url = "citeseer.ist.psu.edu/753028.html" }
Citations (may not include all citations):
116   Topic detection and tracking pilot study: Final report - Allan, Carbonell et al. - 1998

Documents on the same site (http://www.cs.cmu.edu/~yanliu/research.htm):   More
A New Boosting Algorithm Using Input-Dependent Regularizer - Rong Jin Rong (2003)   (Correct)
Segmentation Conditional Random Fields (SCRFs): A.. - Liu, Carbonell..   (Correct)
ON PREDICTING RARE CLASSES WITH SVM ENSEMBLES IN SCENE.. - School Of Computer   (Correct)

Online articles have much greater impact   More about CiteSeer.IST   Add search form to your site   Submit documents   Feedback  

CiteSeer.IST - Copyright Penn State and NEC