Unsupervised Lexical Entry Acquisition Model based on Representation of Human Mental Lexicon
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Yu, Wonhee | - |
dc.contributor.author | Park, Doo-Soon | - |
dc.contributor.author | Suh, Taeweon | - |
dc.contributor.author | Lim, Heuiseok | - |
dc.date.accessioned | 2021-09-07T10:59:11Z | - |
dc.date.available | 2021-09-07T10:59:11Z | - |
dc.date.created | 2021-06-14 | - |
dc.date.issued | 2011-07 | - |
dc.identifier.issn | 1343-4500 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/112076 | - |
dc.description.abstract | This paper proposes a computational lexical entry acquisition model based on a representation model of the mental lexicon. The proposed model acquires lexical entries from a raw corpus by unsupervised learning, like human beings. The model is composed of full-form and morpheme acquisition modules. In the full-form acquisition module, core full-forms are automatically acquired according to the frequency and recency thresholds. In the morpheme acquisition module, a repeatedly occurring substring in different full-forms is chosen as a candidate morpheme. Then, the candidate is corroborated as a morpheme by using the entropy measure of syllables in the string. We tested the model with a Korean language raw corpus as large as about 16 million Korean full-forms. The test results show that the model successively acquires major Korean language full-forms and morphemes, with an average precision of 100% and 99.04%, respectively. In addition, we observed a vocabulary spurt during learning, which is a phenomenon peculiar to children's language learning process. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | INT INFORMATION INST | - |
dc.subject | REPETITION | - |
dc.title | Unsupervised Lexical Entry Acquisition Model based on Representation of Human Mental Lexicon | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Suh, Taeweon | - |
dc.contributor.affiliatedAuthor | Lim, Heuiseok | - |
dc.identifier.scopusid | 2-s2.0-84860124432 | - |
dc.identifier.wosid | 000295904700005 | - |
dc.identifier.bibliographicCitation | INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL, v.14, no.7, pp.2229 - 2241 | - |
dc.relation.isPartOf | INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL | - |
dc.citation.title | INFORMATION-AN INTERNATIONAL INTERDISCIPLINARY JOURNAL | - |
dc.citation.volume | 14 | - |
dc.citation.number | 7 | - |
dc.citation.startPage | 2229 | - |
dc.citation.endPage | 2241 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalWebOfScienceCategory | Engineering, Multidisciplinary | - |
dc.subject.keywordPlus | REPETITION | - |
dc.subject.keywordAuthor | Mental Lexicon | - |
dc.subject.keywordAuthor | Lexical Acquisition | - |
dc.subject.keywordAuthor | Language Learning | - |
dc.subject.keywordAuthor | Machine Readable Dictionary | - |
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