Semantic Scholar Open Access 2023 3 sitasi

Large-scale weighted sequence alignment for the study of intertextuality in Finnic oral folk poetry

Maciej Janicki

Abstrak

The digitization of large archival collections of oral folk poetry in Finland and Estonia has opened possibilities for large-scale quantitative studies of intertextuality. As an initial methodological step in this direction, I present a method for pairwise line-by-line comparison of poems using the weighted sequence alignment algorithm (a.k.a. ‘weighted edit distance’). The main contribution of the paper is a novel description of the algorithm in terms of matrix operations, which allows for much faster alignment of a poem against the entire corpus by utilizing modern numeric libraries and GPU capabilities. This way we are able to compute pairwise alignment scores between all pairs from among a corpus of over 280,000 poems. The resulting table of over 40 million pairwise poem similarities can be used in various ways to study the oral tradition. Some starting points for such research are sketched in the latter part of the article.

Topik & Kata Kunci

Penulis (1)

M

Maciej Janicki

Format Sitasi

Janicki, M. (2023). Large-scale weighted sequence alignment for the study of intertextuality in Finnic oral folk poetry. https://doi.org/10.46298/jdmdh.11390

Akses Cepat

Lihat di Sumber doi.org/10.46298/jdmdh.11390
Informasi Jurnal
Tahun Terbit
2023
Bahasa
en
Total Sitasi
Sumber Database
Semantic Scholar
DOI
10.46298/jdmdh.11390
Akses
Open Access ✓