Learning Turkish Hypernymy Using Word Embeddings

Basit Öğe Kaydı
dc.WoS.categoriesComputer Science, Artificial Intelligence; Computer Science, Interdisciplinary Applicationsen_US
dc.authorid0000-0002-7764-2891en_US
dc.contributor.authorYıldırım, Savaş
dc.contributor.authorYıldız, Tuğba
dc.date.accessioned2020-12-10T07:17:46Z
dc.date.available2020-12-10T07:17:46Z
dc.date.issued2018
dc.description.abstractRecently, Neural Network Language Models have been effectively applied to many types of Natural Language Processing (NLP) tasks. One popular type of tasks is the discovery of semantic and syntactic regularities that support the researchers in building a lexicon. Word embedding representations are notably good at discovering such linguistic regularities. We argue that two supervised learning approaches based on word embeddings can be successfully applied to the hypernym problem, namely, utilizing embedding offsets between word pairs and learning semantic projection to link the words. The offset-based model classifies offsets as hypernym or not. The semantic projection approach trains a semantic transformation matrix that ideally maps a hyponym to its hypernym. A semantic projection model can learn a projection matrix provided that there is a sufficient number of training word pairs. However, we argue that such models tend to learn is-a-particular-hypernym relation rather than to generalize is-a relation. The embeddings are trained by applying both the Continuous Bag-of Words and the Skip-Gram training models using a huge corpus in Turkish text. The main contribution of the study is the development of a novel and efficient architecture that is well-suited to applying word embeddings approaches to the Turkish language domain. We report that both the projection and the offset classification models give promising and novel results for the Turkish Language.en_US
dc.fullTextLevelFull Texten_US
dc.identifier.issn1875-6883
dc.identifier.issn1875-6891
dc.identifier.urihttps://hdl.handle.net/11411/2820
dc.identifier.wosWOS:000430620000028en_US
dc.identifier.wosqualityQ3en_US
dc.indekslendigikaynakWeb of Scienceen_US
dc.issue1en_US
dc.language.isoenen_US
dc.nationalInternationalen_US
dc.numberofauthors200+en_US
dc.pages371-383en_US
dc.publisherATLANTIS PRESSen_US
dc.relation.ispartofINTERNATIONAL JOURNAL OF COMPUTATIONAL INTELLIGENCE SYSTEMSen_US
dc.relation.publicationcategoryMakale - Uluslararası Hakemli Dergi - Kurum Öğretim Elemanıen_US
dc.rightsinfo:eu-repo/semantics/openAccessen_US
dc.subjectWord Embeddingsen_US
dc.subjectSemantic Relation Projectionen_US
dc.subjectSemantic Relation Classificationen_US
dc.titleLearning Turkish Hypernymy Using Word Embeddings
dc.typeArticle
dc.volume11en_US

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