A new classification of masks from Guerrero discovered in the Great Temple of Tenochtitlan

Summary

This paper focuses on a new kind of typological analysis based on a quantitative procedure called Spectral Clustering. This technique uses Graph Theory to analyse the eigenstructure of an affinity matrix in order to partition data points into disjoint clusters. The original algorithms were developed a decade ago by mathematicians and machine learning professionals. To the best of our knowledge, this technique has not been applied before in archaeology despite its proven performance in partitioning a collection of artefacts into meaningful groups.

As a study case we choose a collection of stone masks from Guerrero but found in the remains of the Sacred Precinct of Tenochtitlan, the main ceremonial Aztec centre. The schematic features of these objects set them apart from other artefacts with more naturalistic style. This has attracted the attention of many specialists and during the last three decades the style of these items have been the subject of intense debate. Through the application of Spectral Clustering we were able to segment this collection into well-defined groups. In the future, this could lead to a better typology of this collection.

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This Resource is Part of the Following Collections

• Society for American Archaeology 80th Annual Meeting, San Francisco, CA (2015)   •
• Crafting the Tenochcan Imperial Identity and Style

Keywords

Spatial Coverage