Threshold Optimization with a Small Number of Samples in Adaptive Information Filtering

  • XIA Ying-Ju, HUANG Xuan-Jing, Hu Tian, WU Li-De
  • Published 2003

Abstract

One special challenge in adaptive information filtering is the problem of extremely sparse data. So it is very important to learn optimal threshold while filtering the input textual stream. In this paper, an algorithm is presented for the threshold optimization. The algorithm learns fast by using few positive samples. Moreover, most of the quantities the… (More)

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