Discovering Continuous Multi-word Expressions in Czech

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F18%3A00109727" target="_blank" >RIV/00216224:14330/18:00109727 - isvavai.cz</a>

Výsledek na webu

<a href="http://doi.org/10.13053/CyS-22-3-3022" target="_blank" >http://doi.org/10.13053/CyS-22-3-3022</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.13053/CyS-22-3-3022" target="_blank" >10.13053/CyS-22-3-3022</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Discovering Continuous Multi-word Expressions in Czech

Popis výsledku v původním jazyce

Multi-word expressions frequently cause incorrect annotations in corpora, since they often contain foreign words or syntactic anomalies. In case of foreign material, the annotation quality depends on whether the correct language of the sequence is detected. In case of inter-lingual homographs, this problem becomes difficult. In the previous work, we created a dataset of Czech continuous multi-word expressions (MWEs). The candidates were discovered automatically from Czech web corpus considering their orthographic variability. The candidates were classified and annotated manually. Afterwards, the dataset was extended automatically by generating all word forms of those MWEs that were annotated as nouns. In this work, we used the dataset as positive examples, we filtered out negative examples from the MWE candidates. We trained a classifier with mean accuracy 92.7%. We have shown that the combined approach slightly outperforms approaches concerning only association measures mainly on MWEs containing inter-lingual homographs and out-of-vocabulary words. The discovery methods can be applied to other languages which encounter orthographic variability in web corpora.

Název v anglickém jazyce

Discovering Continuous Multi-word Expressions in Czech

Popis výsledku anglicky

Multi-word expressions frequently cause incorrect annotations in corpora, since they often contain foreign words or syntactic anomalies. In case of foreign material, the annotation quality depends on whether the correct language of the sequence is detected. In case of inter-lingual homographs, this problem becomes difficult. In the previous work, we created a dataset of Czech continuous multi-word expressions (MWEs). The candidates were discovered automatically from Czech web corpus considering their orthographic variability. The candidates were classified and annotated manually. Afterwards, the dataset was extended automatically by generating all word forms of those MWEs that were annotated as nouns. In this work, we used the dataset as positive examples, we filtered out negative examples from the MWE candidates. We trained a classifier with mean accuracy 92.7%. We have shown that the combined approach slightly outperforms approaches concerning only association measures mainly on MWEs containing inter-lingual homographs and out-of-vocabulary words. The discovery methods can be applied to other languages which encounter orthographic variability in web corpora.

Druh

J_imp - Článek v periodiku v databázi Web of Science

CEP obor

—

OECD FORD obor

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

Projekt

<a href="/cs/project/EF16_013%2F0001781" target="_blank" >EF16_013/0001781: LINDAT/CLARIN - Výzkumná infrastruktura pro jazykové technologie - rozšíření repozitáře a výpočetní kapacity</a><br>

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 periodika

Computación y Sistemas

ISSN

1405-5546

e-ISSN

2007-9737

Svazek periodika

22

Číslo periodika v rámci svazku

3

Stát vydavatele periodika

MX - Spojené státy mexické

Počet stran výsledku

8

Strana od-do

845-852

Kód UT WoS článku

000471005100013

EID výsledku v databázi Scopus

2-s2.0-85055482087