Scopus
YÖKSİS DOI Eşleşti
SJR Q1
A new approach on search for similar documents with multiple categories using fuzzy clustering
Expert Systems with Applications · Mayıs 2008
YÖKSİS Kayıtları
A new approach on search for similar documents with multiple categories using fuzzy clustering
Expert Systems with Applications · 2008 SCI-Expanded
Doç. Dr. KEMAL TÜTÜNCÜ →
YÖKSİS Kayıtları — ISSN Eşleşmesi
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Web based medical decision support system application of Coronary Heart Disease diagnosis with Boolean functions minimization method
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Modeling and prediction of surface roughness in turning operations using artificial neural network and multiple regression method
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Prof. Dr. MEHMET ÇUNKAŞ →
A fuzzy clustering approach for finding similar documents using a novel similarity measure
2007 ISSN: 0957-4174 SCI-Expanded 22 atıf
Doç. Dr. KEMAL TÜTÜNCÜ →
A new approach on search for similar documents with multiple categories using fuzzy clustering
2008 ISSN: 0957-4174 SCI-Expanded
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Organizational strategy development in distribution channel management using fuzzy AHP and hierarchical fuzzy TOPSIS
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Artificial neural network and fuzzy expert system comparison for prediction of performance and emission parameters on a gasoline engine
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Artificial neural network and fuzzy expert system comparison for prediction of performance and emission parameters on a gasoline engine
2011 ISSN: 0957-4174 SCI-Expanded 4 atıf
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Fuzzy expert system design for operating room air-condition control systems
2009 ISSN: 0957-4174 SCI-Expanded 29 atıf Q1
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Prognosis of prostate cancer by artificial neural networks
2010 ISSN: 0957-4174 SCI-Expanded 30 atıf Q1
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Prediction of diesel engine performance using biofuels with artificial neural network
2010 ISSN: 0957-4174 SCI-Expanded 53 atıf Q1
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The effects of fuzzy control of magnetic flux on magnetic filter performance and energy consumption
2010 ISSN: 0957-4174 SCI-Expanded 5 atıf Q1
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Artificial neural network and fuzzy expert system comparison for prediction of performance and emission parameters on a gasoline engine
2011 ISSN: 0957-4174 SCI-Expanded 24 atıf Q1
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Anesthetic gas control with neuro fuzzy system in anesthesia
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An Adaptive Network Based Fuzzy Inference System ANFIS for the prediction of stock market return The case of the Istanbul Stock Exchange
2010 ISSN: 09574174 SCI-Expanded
Prof. Dr. MELEK ACAR →
Predicting direction of stock price index movement using artificial neural networks and support vector machines The sample of the Istanbul Stock Exchange
2011 ISSN: 09574174 SCI-Expanded
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Predicting bank financial failures using neural networks support vector machines and multivariate statistical methods A comparative analysis in the sample of savings deposit insurance fund SDIF transferred banks in Turkey
2009 ISSN: 09574174 SCI-Expanded
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The design of ultrasonic therapy device via fuzzy logic
2011 ISSN: 09574174 SCI-Expanded
Öğr. Gör. SEMA YILDIRIM →
Assessment of exercise stress testing with artificial neural network in determining coronary artery disease and predicting lesion localization
2009 ISSN: 09574174 SCI-Expanded
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2008 ISSN: 0957-4174 SCI-Expanded 85 atıf Q1
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Makale Bilgileri
ISSN09574174
Yayın TarihiMayıs 2008
Cilt / Sayfa34 · 2545-2554
Scopus ID2-s2.0-38649135048
Özet
Searching for similar document has an important role in text mining and document management. In whether similar document search or in other text mining applications generally document classification is focused and class or category that the documents belong to is tried to be determined. The aim of the present study is the investigation of the case which includes the documents that belong to more than one category. The system used in the present study is a similar document search system that uses fuzzy clustering. The situation of belonging to more than one category for the documents is included by this system. The proposed approach consists of two stages to solve multicategories problem. The first stage is to find out the documents belonging to more than one category. The second stage is the determination of the categories to which these found documents belong to. For these two aims α-threshold Fuzzy Similarity Classification Method (α-FSCM) and Multiple Categories Vector Method (MCVM) are proposed as written order. Experimental results showed that proposed system can distinguish the documents that belong to more than one category efficiently. Regarding to the finding which documents belong to which classes, proposed system has better performance and success than the traditional approach. © 2007 Elsevier Ltd. All rights reserved.
Yazarlar (3)
1
Ridvan Saraçoǧlu
2
Kemal Tutuncu
3
Novruz Allahverdi
Anahtar Kelimeler
Document similarity
Fuzzy clustering
Multiple categories
Similarity search
Text mining
Kurumlar
Selçuk Üniversitesi
Selçuklu Turkey
Scimago Dergi (ISSN Eşleşmesi)
Expert Systems with Applications
Q1
SJR Skoru1,854
H-Index290
YayıncıElsevier Ltd
ÜlkeUnited Kingdom
Artificial Intelligence (Q1)
Computer Science Applications (Q1)
Engineering (miscellaneous) (Q1)
Metrikler
30
Atıf
3
Yazar
5
Anahtar Kelime