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      Squeezing the ensemble pruning: Faster and more accurate categorization for news portals

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      Author(s)
      Toraman, Cağrı
      Can, Fazlı
      Date
      2012
      Source Title
      Advances in Information Retrieval, 34th European Conference on IR Research, ECIR 2012
      Print ISSN
      0302-9743
      Publisher
      Springer
      Volume
      7224
      Pages
      508 - 511
      Language
      English
      Type
      Conference Paper
      Item Usage Stats
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      Abstract
      Recent studies show that ensemble pruning works as effective as traditional ensemble of classifiers (EoC). In this study, we analyze how ensemble pruning can improve text categorization efficiency in time-critical real-life applications such as news portals. The most crucial two phases of text categorization are training classifiers and assigning labels to new documents; but the latter is more important for efficiency of such applications. We conduct experiments on ensemble pruning-based news article categorization to measure its accuracy and time cost. The results show that our heuristics reduce the time cost of the second phase. Also we can make a trade-off between accuracy and time cost to improve both of them with appropriate pruning degrees. © 2012 Springer-Verlag Berlin Heidelberg.
      Keywords
      Ensemble pruning
      Ensemble of classifiers
      Ensemble pruning
      News articles
      Real-life applications
      Second phase
      Text categorization
      Time cost
      Information retrieval
      Text processing
      Permalink
      http://hdl.handle.net/11693/28223
      Published Version (Please cite this version)
      http://dx.doi.org/10.1007/978-3-642-28997-2_52
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      • Department of Computer Engineering 1435
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