Interpreting

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• Literary Network of the National Awakening Based on the Correspondence of Koidula and Kreutzwald

  This workflow was created to analyse the correspondence between Friedrich Reinhold Kreutzwald and Lydia Koidula from the years 1867–1873 and to map which people appear most frequently in the literary network of the National Awakening on the basis of these letters. The correspondence is one of the most important sources in Estonian literary history, reflecting the development of the national movement, cultural contacts, and relationships between authors. The workflow makes it possible to automatically identify personal names in a text corpus, clean and standardise name forms, and...

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• Analysis of Regional and Temporal Patterns in Estonian Instrumental Folk Music

  This workflow enables the analysis of the regional and temporal distribution of instruments and instrumental tunes in a dataset of Estonian instrumental folk music. During the workflow, the metadata of the archival dataset are cleaned, instrument and place names are standardised, and broader analytical instrument categories are created as needed. The frequencies of instruments and folk tunes are then calculated by county and time period. The results are presented as frequency tables, diagrams, and maps, which help make visible patterns that would be difficult to detect by looking at individual records.

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• Pattern Analysis of Striped Skirts

  This workflow describes how image-based patterns are compared using machine learning methods. The aim is to investigate the pattern logic that characterised Estonian striped skirts of the 18th–19th centuries and to examine how these patterns relate to striped, glazed-surface woollen callimanco fabrics produced at the Norwich factory in England. The workflow combines digital humanities approaches with machine learning. For analysing large image datasets, we use machine learning models designed for visual pattern recognition, specifically convolutional neural networks (CNNs).

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• Comparative Topic Analysis of Ukrainian and Estonian Folk Songs Using AI Translation and Computational Methods

  The aim of the research was to identify thematic overlap, cultural similarities, and unique topics in Ukrainian and Estonian folk songs using computational methods, particularly LLM translation and LDA topic modelling. Although the two nations belong to different linguistic and cultural traditions (Finnic and East Slavic), they shared periods of historical contact that may be reflected in their folklore. From the early Middle Ages, both regions were connected through northern–southern trade networks...

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