Scopus
YÖKSİS Eşleşti
A fuzzy clustering approach for finding similar documents using a novel similarity measure
Expert Systems with Applications · Ekim 2007
YÖKSİS Kayıtları
A fuzzy clustering approach for finding similar documents using a novel similarity measure
Expert Systems with Applications · 2007 SCI-Expanded 22 atıf
DOÇENT KEMAL TÜTÜNCÜ →
Makale Bilgileri
DergiExpert Systems with Applications
Yayın TarihiEkim 2007
Cilt / Sayfa33 · 600-605
Scopus ID2-s2.0-33847660060
Özet
Searching for similar documents has a crucial role in document management. This paper aims for developing a fast and high quality method of searching similar documents based on fuzzy clustering in large document collections. In order to perform these requirements, a two layers structure is proposed. Formerly, finding the similarity in documents is based on the strategy that uses word-by-word comparison. The proposed method in this study uses two layers structure and lets the documents pass through it to find the similarities. In this system, predefined fuzzy clusters are used to extract feature vectors of related documents for finding similar documents of them. Similarity measure is estimated based on these vectors. To do this, a distance based similarity measure is proposed. It has been seen in empirical results that the proposed system uses new similarity measure and has better performance compared with conventional similarity measurement systems. © 2006 Elsevier Ltd. All rights reserved.
Yazarlar (3)
1
Ridvan Saraçoǧlu
2
Kemal Tutuncu
3
Novruz Allahverdi
Anahtar Kelimeler
Distance based similarity
Document similarity
Fuzzy clustering
Fuzzy similarity measure
Text mining
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Metrikler
49
Atıf
3
Yazar
5
Anahtar Kelime