长春工程学院学报：自然科学版
長春工程學院學報：自然科學版
장춘공정학원학보：자연과학판
Journal of Changchun Institute of Technology（Social Science Edition)
2012年
1期
111-114
,共4页
数据挖掘%关联规则%时间序列%频繁时序
數據挖掘%關聯規則%時間序列%頻繁時序
수거알굴%관련규칙%시간서렬%빈번시서
data mining%association rules%time-series%frequent time-series
针对时间序列,研究和分析时序关联规则挖掘,提出时序关联规则数据挖掘的基于滑动窗口和时序树特殊结构的新的挖掘算法,并利用该算法挖掘超过给定支持数阈值频繁时序,为用户的决策支持及趋势预测提供支持,并通过实验验证算法的有效性和实用性。
針對時間序列,研究和分析時序關聯規則挖掘,提齣時序關聯規則數據挖掘的基于滑動窗口和時序樹特殊結構的新的挖掘算法,併利用該算法挖掘超過給定支持數閾值頻繁時序,為用戶的決策支持及趨勢預測提供支持,併通過實驗驗證算法的有效性和實用性。
침대시간서렬,연구화분석시서관련규칙알굴,제출시서관련규칙수거알굴적기우활동창구화시서수특수결구적신적알굴산법,병이용해산법알굴초과급정지지수역치빈번시서,위용호적결책지지급추세예측제공지지,병통과실험험증산법적유효성화실용성。
According to the time series,the research and analysis of time-series association rules mining has been discussed in this paper,and a new algorithm for time-series association rules data mining based on sliding window and time-series tree with special structure has been proposed.By using this algorithm,the mining to frequent time-series which exceeds a given support count threshold has been acted to provide the decision support and trend prediction for users.The experiment results prove the validity and practicability of this algorithm.
