Study on the Similarity Query Based on LCSS over Data Stream Window

Shaopeng Wang, Yingyou Wen, Hong Zhao
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引用次数: 2

Abstract

Aiming at the problem that the NAIVE algorithm which is taken to handle the similarity query based on LCSS over data stream window (SQLSW) cannot get query results until calculations on all elements in the full dynamic programming matrix are finished, the SQLSW query processing algorithm based on Possible Solution domain optimization strategy (SQLSW-PS) is proposed. It defines possible solution (PS) domain of the dynamic programming matrix about every window. Based on characters of matrix members in the PS domain and the similarity query, it can get query result on the condition that the LCSS similarity function value has not been obtained yet, and reduce lots of computations related to matrix members. It is revealed by extensive experiments that the SQLSW-PS outperforms current algorithms in time, and is effective in handling the SQLSW query.
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基于LCSS的数据流窗口相似性查询研究
针对采用朴素算法处理基于LCSS的数据流窗口相似性查询(SQLSW)需要对全动态规划矩阵中的所有元素进行计算后才能得到查询结果的问题,提出了基于可能解域优化策略(SQLSW- ps)的SQLSW查询处理算法。定义了每个窗口的动态规划矩阵的可能解域。基于PS域中矩阵成员的特征和相似度查询,可以在尚未得到LCSS相似函数值的情况下得到查询结果,减少了与矩阵成员相关的大量计算。大量的实验表明,SQLSW- ps在时间上优于现有的算法,在处理SQLSW查询方面是有效的。
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