Lexical data mining-based approach for the self-enrichment of LMF standardized dictionaries: Case of the syntactico-semantic knowledge

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10441625" target="_blank" >RIV/00216208:11320/21:10441625 - isvavai.cz</a>

Výsledek na webu

<a href="https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Itcfb.rlbg" target="_blank" >https://verso.is.cuni.cz/pub/verso.fpl?fname=obd_publikace_handle&handle=Itcfb.rlbg</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1002/cpe.6312" target="_blank" >10.1002/cpe.6312</a>

Jazyk výsledku

angličtina

Název v původním jazyce

Lexical data mining-based approach for the self-enrichment of LMF standardized dictionaries: Case of the syntactico-semantic knowledge

Popis výsledku v původním jazyce

The LMF ISO standard provides a large cover of lexical knowledge using a fine structure. However, like most of the electronic dictionaries, the available normalized LMF dictionaries comprise only basic morpho-syntactic and semantic knowledge, such as the meanings of lexical entries through the definitions and the associated examples, and sometimes the indication of the synonyms and antonyms. Other sophisticated knowledge, such as the syntactic behaviors, semantic classes and syntactico-semantic links, which are scarce, requires a high expertise and its adding to dictionaries is expensive. In fact in this paper, we propose an approach of lexical data mining of the widely available textual content associated with the meanings, notably in the normalized LMF dictionaries, in order to perform the self-enrichment of these dictionaries. First, we contribute to the enrichment of the syntactic behaviors by linking them to the suitable meanings. Second, we focus on the enrichment of the meanings of LMF lexical entries with semantic classes based on the Gaston Gross semantic classification. Finally, we establish the syntactico-semantic links based on the results of the syntactic and semantic enrichment processes. The proposed approach has been consolidated by an experimentation carried out on an available normalized LMF dictionary for Arabic language.

Název v anglickém jazyce

Lexical data mining-based approach for the self-enrichment of LMF standardized dictionaries: Case of the syntactico-semantic knowledge

Popis výsledku anglicky

The LMF ISO standard provides a large cover of lexical knowledge using a fine structure. However, like most of the electronic dictionaries, the available normalized LMF dictionaries comprise only basic morpho-syntactic and semantic knowledge, such as the meanings of lexical entries through the definitions and the associated examples, and sometimes the indication of the synonyms and antonyms. Other sophisticated knowledge, such as the syntactic behaviors, semantic classes and syntactico-semantic links, which are scarce, requires a high expertise and its adding to dictionaries is expensive. In fact in this paper, we propose an approach of lexical data mining of the widely available textual content associated with the meanings, notably in the normalized LMF dictionaries, in order to perform the self-enrichment of these dictionaries. First, we contribute to the enrichment of the syntactic behaviors by linking them to the suitable meanings. Second, we focus on the enrichment of the meanings of LMF lexical entries with semantic classes based on the Gaston Gross semantic classification. Finally, we establish the syntactico-semantic links based on the results of the syntactic and semantic enrichment processes. The proposed approach has been consolidated by an experimentation carried out on an available normalized LMF dictionary for Arabic language.

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

—

Návaznosti

—

Rok uplatnění

2021

Kód důvěrnosti údajů

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

Název periodika

Concurrency Computation Practice and Experience

ISSN

1532-0626

e-ISSN

1532-0634

Svazek periodika

33

Číslo periodika v rámci svazku

17

Stát vydavatele periodika

GB - Spojené království Velké Británie a Severního Irska

Počet stran výsledku

32

Strana od-do

e6312

Kód UT WoS článku

000640935900001

EID výsledku v databázi Scopus

2-s2.0-85104407123