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Dergiler / Sakarya University Journal of Science / 2026 / Volume: 17 Issue: 1

İnternet Ortamındaki Tüketici Yorumlarından Özet Bilgi Çıkarımı

Abstract Information Extraction From Consumer's Comments On Internet Media

Kadriye Ergün
Cemalettin Kubat
Gültekin Çağıl
Raşit Cesur
Sayfa
—
Yayın Tarihi
2013-04-01
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Yapay Zeka Hızlı Bakış & Çıkarımlar

AI Insight
⚡ TL;DR(1 Cümlede Hızlı Çıkarım)

When any inquiry is made from these data depending on any property of product, numerical information which indicates the degree of satisfaction about this property is obtained.

📌 3 Maddede Bu Makale

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Amaç & Hipotez:In this study, a system developed to summarize by automatically evaluating comments about product with using text mining techniques will be described.
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Temel Bulgular & Veri:The data has been primarily went through morphological analysis process, because they are texts written in natural language.
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Sonuç & Katkı:When any inquiry is made from these data depending on any property of product, numerical information which indicates the degree of satisfaction about this property is obtained.
🔬Tür:Research Article
📍Kapsam:Genişletilmiş Akademik Örneklem
⚙️Değişkenler:Text Mining · Information Extraction · Natural Language Processing

Özet

In this study, a system developed to summarize by automatically evaluating comments about product with using text mining techniques will be described. The data has been primarily went through morphological analysis process, because they are texts written in natural language. Words and adjectives meaning positive or negative are determined. They show product features in texts. The tree structure is established according to Turkish grammar rules as subordinate and modified words are designated. The software which uses the depth-first search algorithm on the tree structure is developed. Data from result of software is stored in the SQL database. When any inquiry is made from these data depending on any property of product, numerical information which indicates the degree of satisfaction about this property is obtained.

Abstract

information extraction from consumer's comments on internet media In this study, a system developed to summarize by automatically evaluating comments about product with using text mining techniques will be described. The data has been primarily went through morphological analysis process, because they are texts written in natural language. Words and adjectives meaning positive or negative are determined. They show product features in texts. The tree structure is established according to Turkish grammar rules as subordinate and modified words are designated. The software which uses the depth-first search algorithm on the tree structure is developed. Data from result of software is stored in the SQL database. When any inquiry is made from these data depending on any property of product, numerical information which indicates the degree of satisfaction about this property is obtained. .

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Bu Makaleye Atıf Yap

Ergün, K., Kubat, C., Çağıl, G., Cesur, R. (2013). İnternet Ortamındaki Tüketici Yorumlarından Özet Bilgi Çıkarımı. Sakarya University Journal of Science, Volume: 17 Issue: 1. https://doi.org/10.16984/saufbed.12964

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Kaynakça (12)

  1. TURAN A.H., “Internet Alışverişi Tüketici Davranışını Belirleyen Etmenler: Geliştirilmiş Teknoloji Kabul Modeli (E-TAM) İle Bir Model Önerisi”, Akademik Bilişim, 2008.
  2. GÜVEN, A., Türkçe Belgelerin Anlam Tabanlı Yöntemlerle Madenciliği, Yıldız Teknik Üniversitesi FBE, Doktora Tezi, 2007.
  3. ÖZYURT Ö., “Türkçe Tabanlı Diyalog Sistemi ve İnternet (Chat) Ortamlarından Bilgi Çıkarımı”, Karadeniz Teknik Üniversitesi Fen Bilimleri Enstitüsü, Yüksek Lisans Tezi, 2006.
  4. SARAÇOĞLU R., TÜTÜNCÜ K., ALLAHVERDİ N., A new approach on search for similar documents with multiple categories using fuzzy clustering, Expert Systems with Applications 34 (2008) 2545–2554, 2008. DELEN D., CROSSLAND M.D., Seeding the survey and analysis of research literature with text mining, Expert Systems with Applications, 34 (2008) 1707–1720, 2008.
  5. ZOHAR, E.Y., Introduction to Text Mining, Supercomputing 2002, Automated Learning Group National Center for Supercomputing Applications, University of Illinois, 2002.
  6. TÜRKEEŞ, M.K., Bilgi Erişiminde Tamlama Temelli Dizinleme, İstanbul Teknik Üniversitesi FBE, Yüksek Lisans Tezi, 2007.
  7. DAŞ, R., Web Kullanıcı Erişim Kütüklerinden Bilgi Çıkarımı, Fırat Üniversitesi FBE, Doktora Tezi, 2008.
  8. BAYKAL A., ÇOŞKUN C., Web Madenciliği Teknikleri, Akademik Bilişim, 2009.
  9. ÖZKAN, Y., Veri Madenciliği Yöntemleri, Papatya Yayıncılık, İstanbul, 2008.
  10. OĞUZLAR, A., Temel Metin Madenciliği, Dora Yayınları, Bursa, 2011. http://www.ii.metu.edu.tr/tr/category/tags/turkcederlem
  11. CEBİROĞLU, G., Sözlüksüz Köke Ulaşma Yöntemi, Yüksek Lisans Tezi, İ.T.Ü. Fen Bilimleri Enstitüsü, 2002.
  12. BENZER, A.İ., Yapay Zeka Uygulamalarında Kullanılan Arama Algoritmalarının Kıyaslanması, Gazi Üniversitesi Bilişim Enstitüsü, Yüksek Lisans Tezi, 200