KEYWORD EXTRACTION BASED ON WORD SYNONYMS USING WORD2VEC
| dc.authorid | OGUL, Iskender Ulgen/0000-0003-4882-5266 | |
| dc.authorid | Ozcan, Caner/0000-0002-2854-4005 | |
| dc.contributor.author | Ogul, Iskender Ulgen | |
| dc.contributor.author | Ozcan, Caner | |
| dc.contributor.author | Hakdagli, Ozlem | |
| dc.date.accessioned | 2024-09-29T16:04:29Z | |
| dc.date.available | 2024-09-29T16:04:29Z | |
| dc.date.issued | 2019 | |
| dc.department | Karabük Üniversitesi | en_US |
| dc.description | 27th Signal Processing and Communications Applications Conference (SIU) -- APR 24-26, 2019 -- Sivas Cumhuriyet Univ, Sivas, TURKEY | en_US |
| dc.description.abstract | Nowadays, the data revealed by the online individuals are increasing exponentially. The raw information that increasing data holds, transformed into meaningful outputs using machine learning and deep learning methods. Generally, supervised learning methods are used for information extraction and classification. Supervised learning is based on the training set that classification algorithms are trained. In the proposed approach, keyword extraction solution is proposed to classify text data more convenient. The developed solution is based on the Word2Vec algorithm, which works by taking into consideration the semantic meaning of the words unlike general approaches that based on word frequency. A new approach, word embedding algorithm named Word2Vec, works by calculating the word weights, semantic relationship, and the final weights of vectors. The obtained keywords are trained with Name Bayes and Decision Trees methods and the performance of the proposed method is shown by classification example. | en_US |
| dc.description.sponsorship | IEEE Turkey Sect,Turkcell,Turkhavacilik Uzaysanayii,Turitak Bilgem,Gebze Teknik Univ,SAP, Detaysoft,NETAS,Havelsan | en_US |
| dc.identifier.doi | 10.1109/siu.2019.8806496 | |
| dc.identifier.isbn | 978-1-7281-1904-5 | |
| dc.identifier.issn | 2165-0608 | |
| dc.identifier.scopus | 2-s2.0-85071991127 | en_US |
| dc.identifier.scopusquality | N/A | en_US |
| dc.identifier.uri | https://doi.org/10.1109/siu.2019.8806496 | |
| dc.identifier.uri | https://hdl.handle.net/20.500.14619/6160 | |
| dc.identifier.wos | WOS:000518994300157 | en_US |
| dc.identifier.wosquality | N/A | en_US |
| dc.indekslendigikaynak | Web of Science | en_US |
| dc.indekslendigikaynak | Scopus | en_US |
| dc.language.iso | tr | en_US |
| dc.publisher | Ieee | en_US |
| dc.relation.ispartof | 2019 27th Signal Processing and Communications Applications Conference (Siu) | en_US |
| dc.relation.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| dc.rights | info:eu-repo/semantics/closedAccess | en_US |
| dc.subject | Spark | en_US |
| dc.subject | Word2Vec | en_US |
| dc.subject | Word Embedding | en_US |
| dc.subject | Keyword Extraction | en_US |
| dc.subject | Text Mining | en_US |
| dc.title | KEYWORD EXTRACTION BASED ON WORD SYNONYMS USING WORD2VEC | en_US |
| dc.type | Conference Object | en_US |
