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Makale detayı · 2023 · article

Comparative Analysis of Globalisation Techniques for Medical Document Classification

Dergi Journal of Soft Computing and Artificial Intelligence
ISSN2717-8226
YÖKSİS OpenAlex Açık erişim · hybrid
Yıl2023
Atıf0OpenAlex
Yüzdelik%1,2
FWCI0,01,00 = dünya ortalaması

Veri kaynağı ayrımı

  • YÖKSİSYÖKSİS makale kaydı
  • YÖKSİS dergi adıJournal of Soft Computing and Artificial Intelligence
  • OpenAlexOpenAlex zenginleştirmesi (özet, atıf, konular)
  • Semantic Scholaratıf sayısı (OpenAlex ile birleştirilmez)

Özet

OpenAlex İngilizce

Medical document classification is one of the important topics of text mining. Globalisation techniques play a major role in text classification. It is also known that globalisation techniques play an important role in text classification. Our aim in the study is to conduct a detailed analysis on two data sets with English and Turkish content by using medical text summaries of Turkish articles. These datasets consist of Turkish and English text summaries of the same articles. To observe how successful local feature selection methods in the field of text classification affect the classification performance on these two equivalent data sets by applying different globalisation techniques. The feature selection methods used are CHI2, MI, OR, WLLR. Globalisation techniques are SUM, AVG, MAX. Classifiers are MNB, DT, and SVM.

Konular

Atıflar

OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.

0atıfOpenAlex · cited_by_count (önbellek / veritabanı)

Yazarlar

2
  1. BEKİR PARLAK 1
  2. SALİH BERKAN AYDEMİR AMASYA ÜNİVERSİTESİ 2