<?xml version="1.0" encoding="utf-8" standalone="yes"?>
<item>
  <id>06097839</id>
  <dt>j</dt>
  <an>06097839</an>
  <augroup>
    <au>Jiang, Xiao-Ping</au>
    <au>Li, Cheng-Hua</au>
    <au>Xiang, Wen</au>
    <au>Zhang, Xin-Fang</au>
  </augroup>
  <ti>Na\"{i}ve Bayesian text classification algorithm in cloud computing environment.</ti>
  <so>J. Comput. Appl. 31, No. 9, 2551-2554 (2011).</so>
  <py>2011</py>
  <pu>Science Press, Beijing</pu>
  <lagroup>
    <la>ZH</la>
  </lagroup>
  <ccgroup>
  </ccgroup>
  <utgroup>
    <ut>cloud computing</ut>
    <ut>parallel computing</ut>
    <ut>mapreduce programming mode</ut>
    <ut>text classification</ut>
    <ut>Na\"{i}ve Bayes algorithm</ut>
  </utgroup>
  <cigroup>
  </cigroup>
  <ligroup>
    <li>doi:10.3724/SP.J.1087.2011.02551</li>
  </ligroup>
  <abgroup>
    <ab>Summary: The major procedures of text classification such as uniform text format expression, training, testing and classifying based on Na\"{i}ve Bayesian text classification algorithm were implemented using MapReduce programming mode. The experiments were given in Hadoop cloud computing environment. The experimental results indicate basically linear speedup with an increasing number of node computers. A recall rate of 86\% was achieved when classifying Chinese Web pages.</ab>
    <rv></rv>
  </abgroup>
</item>