| Finding Recently Frequent Items over Online Data Streams |
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| 作者姓名： | 尹志武 黄上腾 |
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| 作者单位： | Department of Computer Science and Engineering Shanghai Jiaotong University，Department of Computer Science and Engineering，Shanghai Jiaotong University，Shanghai 200041，Shanghai 200041 |
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| 摘 要： | In this paper, a new algorithm HCOUNT+ is proposed to find frequent items over data stream based on the HCOUNT algorithm. The new algorithm adopts aided measures to improve the precision of HCOUNT greatly. In addition, HCOUNT+ is introduced to time critical applications and a novel sliding windows-based algorithm SL-HCOUNT+ is proposed to mine the most frequent items occurring recently. This algorithm uses limited memory (nB·(1+α)·eε·ln-M/lnρ(α<1) counters), requires constant processing time per packet (only (1+α)·ln·-M/lnρ(α<1) counters are updated), makes only one pass over the streaming data, and is shown to work well in the experimental results.
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| 关 键 词： | 计算机技术 网络 在线数据 计算方法 |
| 收稿时间： | 2006-08-20 |
Finding Recently Frequent Items over Online Data Streams |
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| YIN Zhi-wu,HUANG Shang-teng.Finding Recently Frequent Items over Online Data Streams[J].Journal of Donghua University,2006,23(6):53-56. |
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| Authors: | YIN Zhi-wu HUANG Shang-teng |
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| Abstract: | In this paper, a new algorithm HCOUNT + is proposed to find frequent items over data stream based on the HCOUNT algorithm. The new algorithm adopts aided measures to improve the precision of HCOUNT greatly. In addition,HCOUNT + is introduced to time critical applications and a novel sliding windows-based algorithm SL-HCOUNT + is proposed to mine the most frequent items occurring recently.This algorithm uses limited memory (nB · (1 +α) · e/ε·In(-M/lnρ)(α＜1) counters), requires constant processing time per packet (only (1+α) · ln(-M/lnρ(α＜1)) counters are updated), makes only one pass over the streaming data,and is shown to work well in the experimental results. |
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| Keywords: | frequent items data streams HCOUNT |
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