Szczegóły publikacji
Opis bibliograficzny
Comparison of text similarity techniques for power of attorney clauses for Polish banks / Karolina WADOWSKA, Piotr A. KOWALSKI // W: Computational intelligence and mathematics for tackling complex problems 6 / eds. László T. Kóczy, Jesús Medina, Piotr A. Kowalski, Eloísa Ramírez-Poussa. — Cham : Springer Nature Switzerland, cop. 2026. — ( Studies in Computational Intelligence ; ISSN 1860-949X ; SCI vol. 1222 ). — Publikacja zawiera materiały z konferencji: 15th European Symposium on Computational Intelligence and Mathematics : 12–15 May 2024, Krakow. — ISBN: 978-3-031-97878-4; e-ISBN: 978-3-031-97879-1. — S. 125–136. — Bibliogr., Abstr. — P. A. Kowalski - dod. afiliacja: Systems Research Institute Polish Academy of Sciences, Warsaw, Poland
Autorzy (2)
Słowa kluczowe
Dane bibliometryczne
| ID BaDAP | 166194 |
|---|---|
| Data dodania do BaDAP | 2026-03-11 |
| DOI | 10.1007/978-3-031-97879-1_14 |
| Rok publikacji | 2026 |
| Typ publikacji | materiały konferencyjne (aut.) |
| Otwarty dostęp |  |
| Wydawca | Springer |
| Czasopismo/seria | Studies in Computational Intelligence |
Abstract
Text similarity techniques allow for close, but not exactly, matching strings to be compared and extracted from bodies of text. This functionality can be considered very useful in automated processing of the documents. In this paper existing algorithms such as Cosine similarity, Levenhstein distance, pre-trained models etc. are compared and summarised. Based on the attorney clauses from the banking sector—the official formats and given template—we consider the effectuality of each of them. An algorithm selection is made not only based on the similarity score, but also the simplicity of the given solution, often considered an advantage in a highly regulated industry. Nevertheless, this study demonstrated that pre-trained models, in certain instances, exhibit a performance that is twice as effective as other techniques that are more readily explicable in a business context.
