扫描仪的新功能:一种从眼球运动数据中揭示参与者策略的工具

S. Popelka, J. Dolezalová, Marketa Beitlova
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引用次数: 6

摘要

该演示描述了ScanGraph的新功能,ScanGraph是一个应用程序,旨在根据访问过的兴趣区域的顺序,发现具有类似刺激阅读策略的参与者。结果使用简单图形的团来可视化。ScanGraph最初于2016年推出。自最初出版以来,增加了新的特性。首先是实现了用于相似度计算的Damerau-Levenshtein算法。用brown - kerbosch算法代替了原始版本中用于查找派系的启发式算法。ScanGraph从开源应用程序OGAMA读取数据,并使用转换工具从SMI BeGaze读取数据,这也允许分析动态刺激。最显著的增强是参与者之间的相似性计算的可能性,不仅针对单一刺激,而且同时针对多个文件。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
New features of scangraph: a tool for revealing participants' strategy from eye-movement data
The demo describes new features of ScanGraph, an application intended for a finding of participants with a similar stimulus reading strategy based on the sequences of visited Areas of Interest. The result is visualised using cliques of a simple graph. ScanGraph was initially introduced in 2016. Since the original publication, new features were added. First of them is the implementation of Damerau-Levenshtein algorithm for similarity calculation. A heuristic algorithm for cliques finding used in the original version was replaced by the Bron-Kerbosch algorithm. ScanGraph reads data from open-source application OGAMA, and with the use of conversion tool also data from SMI BeGaze, which allows analysing dynamic stimuli as well. The most prominent enhancement is the possibility of similarity calculation among participants not only for a single stimulus but for multiple files at once.
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