基于主动搜寻兼序列自归纳机制的数据挖掘算法研究

乔立龙; 刘法胜

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基于主动搜寻兼序列自归纳机制的数据挖掘算法研究

更新时间：2023-10-30

- 基于主动搜寻兼序列自归纳机制的数据挖掘算法研究
- The research on data mining algorithm based on active search and sequence self induction mechanism
- 新一代信息技术 2023年页码：1-5
- 作者机构：
  
  1.乔立龙山东外事职业大学威海乳山264504
  2.刘法胜山东外事职业大学威海乳山264504
- 作者简介：
  
  乔立龙（1981-），男，山东济宁人，副教授，主要研究方向：数据挖掘、计算机网络；邮箱：rainysunny@126.com
  刘法胜（1957-），男，山东临朐人，博士生导师，主要研究方向：熵优化方法与应用；智能交通。
- 基金信息：
- DOI：
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乔立龙,刘法胜.基于主动搜寻兼序列自归纳机制的数据挖掘算法研究[J].新一代信息技术,

LiLongQiao,FaShengLiu.The research on data mining algorithm based on active search and sequence self induction mechanism[J].New Generation of Information Technology,
乔立龙,刘法胜.基于主动搜寻兼序列自归纳机制的数据挖掘算法研究[J].新一代信息技术, DOI：10.3969/j.issn.2096-6091.XXXX.XX.001.

LiLongQiao,FaShengLiu.The research on data mining algorithm based on active search and sequence self induction mechanism[J].New Generation of Information Technology, DOI：10.3969/j.issn.2096-6091.XXXX.XX.001.

摘要

为了解决大数据环境下数据挖掘技术因广泛采用了序列自归纳模型来反映实时信息，数据挖掘性能较低，且在信息序列的全局整体预测上准确性不高，用户对数据进行整体性挖掘不方便等缺点，本文提出了基于主动搜寻兼序列自归纳的全局模型构建方法，通过全局主动搜寻方式对构建的数据序列模型进行拟合，并在数据序列模型中引入基于频繁主动机制来改进搜索路径，提高了算法搜索的效率。仿真实验表明，本文提出的主动搜寻兼序列自归纳机制能够有效的改善数据挖掘的效率，特别是在数据节点数量较多的时候，可以较好的节约数据挖掘获取信息的时间，对大数据挖掘中存在的效率较低的问题有一定的借鉴意义。

Abstract

In order to solve the large data mining technology is widely used in the sequence from the inductive model reflect the lower performance of real-time information and the sequence information of the overall prediction accuracy is not high,bring convenient for the user to the data mining,we proposed the method based on active search and sequence self induction model in this paper construction, through the global active search mode to fit the construction sequence of data model, then in the data sequence model is introduced based on frequent active mechanism to improve search path, which greatly improved the efficiency of search algorithm。 Simulation experiments shows that the active search and sequence since the inductive mechanism can effectively improve the data mining efficiency, especially when there are a large number of node data,which can save a lot of time for data mining or obtaining information, and it also has certain reference significance for the low efficiency of the existing data mining problems.

关键词

数据挖掘序列自归纳主动搜寻数据序列模型

Keywords

data miningsequence self inductionactive searchdata sequence model

references

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