Semi-Automatic Construction of Word-Formation Networks (for Polish and Spanish)

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F18%3A10390174" target="_blank" >RIV/00216208:11320/18:10390174 - isvavai.cz</a>

Výsledek na webu

<a href="http://www.lrec-conf.org/proceedings/lrec2018/pdf/231.pdf" target="_blank" >http://www.lrec-conf.org/proceedings/lrec2018/pdf/231.pdf</a>

DOI - Digital Object Identifier

—

Jazyk výsledku

angličtina

Název v původním jazyce

Semi-Automatic Construction of Word-Formation Networks (for Polish and Spanish)

Popis výsledku v původním jazyce

The paper presents a semi-automatic method for the construction of derivational networks. The proposed approach applies a sequential pattern mining technique in order to construct useful morphological features in an unsupervised manner. The features take the form of regular expressions and later are used to feed a machine-learned ranking model. The network is constructed by applying resulting model to sort the lists of possible base words and selecting the most probable ones. This approach, besides relatively small training set and a lexicon, does not require any additional language resources such as a list of alternations groups, POS tags etc. The proposed approach is applied to the lexeme sets of two languages, namely Polish and Spanish, which results in the establishment of two novel word-formation networks. Finally, the network constructed for Polish is merged with the derivational connections extracted from the Polish WordNet and those resulting from the derivational rules developed by a linguist

Název v anglickém jazyce

Semi-Automatic Construction of Word-Formation Networks (for Polish and Spanish)

Popis výsledku anglicky

The paper presents a semi-automatic method for the construction of derivational networks. The proposed approach applies a sequential pattern mining technique in order to construct useful morphological features in an unsupervised manner. The features take the form of regular expressions and later are used to feed a machine-learned ranking model. The network is constructed by applying resulting model to sort the lists of possible base words and selecting the most probable ones. This approach, besides relatively small training set and a lexicon, does not require any additional language resources such as a list of alternations groups, POS tags etc. The proposed approach is applied to the lexeme sets of two languages, namely Polish and Spanish, which results in the establishment of two novel word-formation networks. Finally, the network constructed for Polish is merged with the derivational connections extracted from the Polish WordNet and those resulting from the derivational rules developed by a linguist

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)

Rok uplatnění

2018

Kód důvěrnosti údajů

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

Název statě ve sborníku

Proceedings of the 11th International Conference on Language Resources and Evaluation (LREC 2018)

ISBN

979-10-95546-00-9

ISSN

—

e-ISSN

neuvedeno

Počet stran výsledku

8

Strana od-do

1853-1860

Název nakladatele

European Language Resources Association

Místo vydání

Paris, France

Místo konání akce

Miyazaki, Japan

Datum konání akce

7. 5. 2018

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

—