Türkçe Metinlerden Anahtar Kelime Çıkarma için Merkezilik Ölçütlerinin İncelenmesi

GÖZ F., MUTLU A., KÜÇÜK K., Temur M., GÜN A.

29. IEEE SİNYAL İŞLEME VE İLETİŞİM UYGULAMALARI KURULTAYI, İstanbul, Turkey, 09 June 2021, (Full Text) identifier identifier

  • Publication Type: Conference Paper / Full Text
  • Doi Number: 10.1109/siu53274.2021.9477807
  • City: İstanbul
  • Country: Turkey
  • Keywords: automatic keyword extraction, graph centrality measures, Turkish document
  • Kocaeli University Affiliated: Yes

Abstract

Keywords are salient words that best describe the content and the topic of a text document. As text documents are not usually annotated by their authors, automatic keyword extraction has become a challenging research topic. In this study, we investigate the performance of graph-centrality measures as initial node weights in graph-based keyword extraction on Tukish bank documents. To this aim, we focus on degree, eigenvector, betweenness, and closeness centralities and investigate their performance on keyword extraction on a 553 bank document dataset in Turkish. The experimental results show eigenvector centrality achieved the best results.