Recchia Gabriel L, Louwerse Max M
Centre for Digital Knowledge, University of Cambridge.
Department of Communication and Information Sciences, Tilburg University.
Cogn Sci. 2016 Nov;40(8):2065-2080. doi: 10.1111/cogs.12311. Epub 2015 Oct 15.
Computational techniques comparing co-occurrences of city names in texts allow the relative longitudes and latitudes of cities to be estimated algorithmically. However, these techniques have not been applied to estimate the provenance of artifacts with unknown origins. Here, we estimate the geographic origin of artifacts from the Indus Valley Civilization, applying methods commonly used in cognitive science to the Indus script. We show that these methods can accurately predict the relative locations of archeological sites on the basis of artifacts of known provenance, and we further apply these techniques to determine the most probable excavation sites of four sealings of unknown provenance. These findings suggest that inscription statistics reflect historical interactions among locations in the Indus Valley region, and they illustrate how computational methods can help localize inscribed archeological artifacts of unknown origin. The success of this method offers opportunities for the cognitive sciences in general and for computational anthropology specifically.
通过比较文本中城市名称同时出现的情况的计算技术,可以通过算法估计城市的相对经度和纬度。然而,这些技术尚未应用于估计来源不明的文物的出处。在这里,我们将认知科学中常用的方法应用于印度河文字,以估计印度河流域文明文物的地理起源。我们表明,这些方法可以根据已知出处的文物准确预测考古遗址的相对位置,并且我们进一步应用这些技术来确定四个出处不明的印章的最可能发掘地点。这些发现表明,铭文统计反映了印度河流域地区各地点之间的历史互动,并且它们说明了计算方法如何有助于定位来源不明的有铭文的考古文物。这种方法的成功为一般认知科学,特别是计算人类学提供了机会。