Testing of Various Approaches for Semiautomatic Parish Records Word Standardization

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216305%3A26230%2F19%3APU135584" target="_blank" >RIV/00216305:26230/19:PU135584 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.fit.vut.cz/research/publication/12047/" target="_blank" >https://www.fit.vut.cz/research/publication/12047/</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-981-15-3412-6_3" target="_blank" >10.1007/978-981-15-3412-6_3</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Testing of Various Approaches for Semiautomatic Parish Records Word Standardization

Popis výsledku v původním jazyce

This paper deals with the clustering of words from parish records. Clustering is essential for downstream standardization. In the past, mostly in the 17th and beginning of 18th century, the names did not have a standard form, thus for further work, it is essential to create clusters of words that have the same meaning. Besides names, the parish records are in the various languages - Czech, German, Latin, so if we want to have relations between people, occupations, or causes of death in one language, we need to standardize it. The first step of standardization is pre-processing, then we compare words, and the last step is classification into clusters. The most crucial step here is a comparison of words. We have tested various approaches like Levenshtein distance and its modifications, Q-grams, Jaro-Winkler, and phonetic codings like Soundex and Double-Metaphone. All those methods have been with types of words that can appear in parish records first and last names, occupation, village, and relationship between people. From these tests, we have chosen the most suitable ways for the clustering of different types of words.

Název v anglickém jazyce

Testing of Various Approaches for Semiautomatic Parish Records Word Standardization

Popis výsledku anglicky

This paper deals with the clustering of words from parish records. Clustering is essential for downstream standardization. In the past, mostly in the 17th and beginning of 18th century, the names did not have a standard form, thus for further work, it is essential to create clusters of words that have the same meaning. Besides names, the parish records are in the various languages - Czech, German, Latin, so if we want to have relations between people, occupations, or causes of death in one language, we need to standardize it. The first step of standardization is pre-processing, then we compare words, and the last step is classification into clusters. The most crucial step here is a comparison of words. We have tested various approaches like Levenshtein distance and its modifications, Q-grams, Jaro-Winkler, and phonetic codings like Soundex and Double-Metaphone. All those methods have been with types of words that can appear in parish records first and last names, occupation, village, and relationship between people. From these tests, we have chosen the most suitable ways for the clustering of different types of words.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

Výsledek vznikl pri realizaci vícero projektů. Více informací v záložce Projekty.

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)<br>S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

JIST: Joint International Semantic Technology Conference

ISBN

978-981-1534-11-9

ISSN

1865-0929

e-ISSN

—

Počet stran výsledku

13

Strana od-do

21-33

Název nakladatele

Springer International Publishing

Místo vydání

Hangzhou

Místo konání akce

Hangzhou, China

Datum konání akce

25. 11. 2019

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

000679332100003