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RAP: A computer program for exploring similarities in behavior sequences using random projections

机译:RAP:一种计算机程序,用于使用随机投影探索行为序列中的相似性

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摘要

A computer program (RAP, for random projection) for exploring similarities between and within sequences of behavior is presented. Given a time window of a sequence, the program calculates a signature, a real-valued vector that is a random projection of the contents of the window (i.e., the codes occurring within it and their relative location, or onset and offset times) into an arbitrary K-dimensional space. Then, given two different time windows from the same sequence or from different sequences, their similarity is computed as an inverse function of the Euclidean distance between their respective signatures. By defining moving (overlapped or not overlapped) windows along each sequence and calculating similarities between every pair of windows from the two sequences, a map of similarities or possible recurrent patterns is obtained; the RAP program represents them as gray-level lattices, which are displayed as mouse-sensitive images in an HTML file. Computation of similarities is based on the random projection method, as presented by Mannila and Sepp?nen (2001), for the analysis of sequences of events. The program reads sequence data files in Sequential Data Interchange Standard (SDIS) format (Bakeman & Quera, 1992, 1995a).
机译:提出了一种计算机程序(RAP,用于随机投影),用于探索行为序列之间和内部的相似性。给定序列的时间窗口,程序将计算出一个签名,即一个实值向量,该向量是窗口内容的随机投影(即,其中出现的代码及其相对位置或开始时间和偏移时间)任意的K维空间。然后,给定来自相同序列或不同序列的两个不同的时间窗口,将它们的相似度计算为它们各自特征之间的欧几里得距离的反函数。通过定义沿每个序列的移动(重叠或不重叠)窗口,并根据两个序列计算每对窗口之间的相似度,可以获得相似度图或可能的重复模式; RAP程序将它们表示为灰度晶格,并在HTML文件中以鼠标敏感图像的形式显示。相似度的计算基于Mannila和Sepp?nen(2001)提出的随机投影方法,用于分析事件序列。该程序读取序列数据交换标准(SDIS)格式的序列数据文件(Bakeman&Quera,1992,1995a)。

著录项

  • 来源
    《Behavior Research Methods》 |2008年第1期|21-32|共12页
  • 作者

    Vicen? Quera;

  • 作者单位

    Departamento de Metodologia de las Ciencias del Comportamiento Universidad de Barcelona Campus Mundet Paseo Valle de Hebròn 171 E-08035 Barcelona Spain;

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  • 原文格式 PDF
  • 正文语种 eng
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  • 入库时间 2022-08-17 23:57:10

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