Scopus İndeksli Yayınlar Koleksiyonu
Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8651
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Conference Object Pyramid Features for Improved Functional Data Classification(Springer Science and Business Media Deutschland GmbH, 2026) Karadeniz, Talha; Maraş, Hadi Hakan; Tokdemir, GülConference Object A Structure-Aware Classifier to Predict Heart Disease(Springer Science and Business Media Deutschland GmbH, 2026) Karadeniz, Talha; Maraş, Hadi Hakan; Tokdemir, GülConference Object Predicting Varicose Vein Recurrence Post-Cyanoacrylate Glue Surgery Using Machine Learning Models(Institute of Electrical and Electronics Engineers Inc., 2025) Karadeniz, Talha; Ahmed, Ruaa Saad Ahmed; Enver, Levent; Sungur, Elif Coskun; Tokdemir, GulConference Object Citation - WoS: 3Citation - Scopus: 4Improvement of General Inquirer Features With Quantity Analysis(Ieee, 2018) Karadeniz, Talha; Dogdu, ErdoganGeneral Inquirer is a word-affect association vocabulary having 11896 entries. Ranging from rectitude to expressiveness, it comes with a flavor of categories. Despite the extensive content, a mapping from "To be or not to be." to "How much?" can be beneficial for word representation. In this work, we apply a method of window based analysis to obtain real valued General Inquirer attributes. Sentence Completion task is chosen to calculate the effectiveness of the operation. After whitening post-process, total cosine similarity convention is followed to concentrate on embedding improvement. Results indicate that our quantity focused variant is considerable.