Tagging unstructured data in turkish language with linked data sources
2015
1 görüntülenme
1 i̇ndirme
Danışman: Doç. Dr. Rıza Cenk Erdur
Özet (EN)
In this thesis, unstructured resumes written in Turkish and semi-structured data retrieved from LinkedIn professional social website are tagged to make them semantic data. Zemberek NLP Library has been chosen following the investigation of natural language processing libraries which would be used in the development of the Turkish natural language processing tool that is used on tagging of text data. Data storage structures that tagged data and the data used in this study are stored in are examined. Triple stores and NoSQL databases are examined in the decision of best options which keep semantic data. In this work, Polyglot Persistence approach is chosen which supports hybrid data infrastructure.
Yazar
Dr. Enes Bulut
Bu Yayına Nasıl Atıf Yapılır
Enes Bulut (Master Thesis). Tagging unstructured data in turkish language with linked data sources, 2015, Ege University.
Anahtar Kelimeler
Lisans
Tüm Hakları Saklıdır
Bu eser belirtilen lisans koşulları altında paylaşılmaktadır.
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