Yazar "Polat, Hüseyin" için Makale Koleksiyonu listeleme
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Arbitrarily distributed data-based recommendations with privacy
Yakut, İbrahim; Polat, Hüseyin (Elsevier Science BV, 2012)Collaborative filtering (CF) systems use customers' preferences about various products to offer recommendations. Providing accurate and reliable predictions is vital for both e-commerce companies and their customers. To ... -
Bölünmüş veri-tabanlı gizliliği koruyan ortak filtreleme sistemlerinde gizli verinin elde edilmesi
Ortak filtreleme algoritmalarının doğru ve güvenilir öneriler üretebilmesi için yeterli veriye ihtiyaç vardır. Bu nedenle yetersiz veriye sahip iki elektronik alışveriş sitesi gizliliklerini ihlal etmeden aralarındaki ... -
A comparison of clustering-based privacy-preserving collaborative filtering schemes
Bilge, Alper; Polat, Hüseyin (Elsevier, 2013)Privacy-preserving collaborative filtering (PPCF) methods designate extremely beneficial filtering skills without deeply jeopardizing privacy. However, they mostly suffer from scalability, sparsity, and accuracy problems. ... -
Deriving private data in partitioned data-based privacy-preserving collaborative filtering systems
Okkalıoğlu, Burcu Demirelli; Koç, Mehmet; Polat, Hüseyin (Gazi University, Fac Engineering Architecture, 2017)Collaborative filtering algorithms need enough data to provide accurate and reliable predictions. Hence, two e-commerce sites holding insufficient data may want to provide predictions on their partitioned data with privacy. ... -
Designing shilling attacks on disguised binary data
Batmaz, Zeynep; Polat, Hüseyin (Inderscience Enterprises LTD, 2017)Privacy-preserving collaborative filtering methods are effectual ways of coping with information overload problem while protecting confidential data. Their success depends on the quality of the collected data. However, ... -
Detecting shilling attacks in private environments
Güneş, İhsan; Polat, Hüseyin (Springer, 2016)Privacy-preserving collaborative filtering algorithms are successful approaches. However, they are susceptible to shilling attacks. Recent research has increasingly focused on collaborative filtering to protect against ... -
Estimating Kriging-based predictions with privacy
Tuğrul, Bülent; Polat, Hüseyin (2013)Kriging is a well-known prediction method. It interpolates the value of an unmeasured location from nearby measured locations. In a traditional Kriging interpolation, a client (an entity that is looking for a prediction ... -
Estimating NBC-based recommendations on arbitrarily partitioned data with privacy
Yakut, İbrahim; Polat, Hüseyin (Elsevier, 2012)Providing partitioned data-based recommendations has been receiving increasing attention due to mutual advantages. In case of limited data, it is not likely to estimate accurate and reliable predictions. Therefore. e-commerce ... -
From existing trends to future trends in privacy-preserving collaborative filtering
Öztürk, Adem; Polat, Hüseyin (Wiley Periodicals, Inc, 2015)The information overload problem, also known as infobesity, forces online vendors to utilize collaborative filtering algorithms. Although various recommendation methods are widely used by many electronic commerce sites, ... -
An improved privacy-preserving DWT-based collaborative filtering scheme
Bilge, Alper; Polat, Hüseyin (Pergamon-Elsevier Science LTD, 2012)Collaborative filtering (CF) is one of the most efficient techniques to produce personalized recommendations and to deal with the information overload of modern times. Although CF techniques have immensely useful filtering ... -
Maskelenmiş Veriler için Kümeleme-Tabanlı Şilin Atak Tespit Yöntemi
Bilge, Alper; Batmaz, Zeynep; Polat, Hüseyin (2016)İnternet'in yaygınlaşması ile beraber hem ortak filtreleme hem de mahremiyetin korunması artan ilgi görmektedir. Mahremiyeti koruyarak doğru önerileri hızlı bir şekilde kullanıcıya sunmak üzere mahremiyettabanlı ortak ... -
A new hybrid recommendation algorithm with privacy
Renckes, Şahin; Polat, Hüseyin; Oysal, Yusuf (Wiley-Blackwell, 2012)Providing accurate and dependable recommendations efficiently while preserving privacy is essential for e-commerce sites to recruit new customers and keep the existing ones. Such sites might be able to increase their sales ... -
P2P collaborative filtering with privacy
Kaleli, Cihan; Polat, Hüseyin (Tubitak Scientific & Technical Research Council Turkey, 2010)With the evolution of the Internet and e-commerce, collaborative filtering (CF) and privacy-preserving collaborative filtering (PPCF) have become popular The goal in CF is to generate predictions with decent accuracy, ... -
Privacy-preserving hybrid collaborative filtering on cross distributed data
Yakut, İbrahim; Polat, Hüseyin (Springer London LTD, 2012)Data collected for collaborative filtering (CF) purposes might be cross distributed between two online vendors, even competing companies. Such corporations might want to integrate their data to provide more precise and ... -
Privacy-Preserving Inverse Distance Weighted Interpolation
Tuğrul, Bülent; Polat, Hüseyin (Springer Heidelberg, 2014)Inverse distance weighted (IDW) interpolation is one of the well-known geo-statistics techniques. On the one hand, one party (server) holding some measurements for specific locations wants to provide predictions; on the ... -
Privacy-preserving kriging interpolation on partitioned data
Tuğrul, Bülent; Polat, Hüseyin (Elsevier Science BV, 2014)Kriging is well-known, frequently applied method in geo-statistics. Its success primarily depends on the total number of measurements for some sample points. If there are sufficient sample points with measurements, kriging ... -
Privacy-Preserving Naive Bayesian Classifier-Based Recommendations on Distributed Data
Kaleli, Cihan; Polat, Hüseyin (Wiley, 2015)Data collected for recommendation purposes might be distributed among various e-commerce sites, which can collaboratively provide more accurate predictions. However, because of privacy concerns, they might not want to work ... -
Privacy-Preserving Random Projection-Based Recommendations Based on Distributed Data
Kaleli, Cihan; Polat, Hüseyin (World Scientific Publ Co Pte LTD, 2013)Providing recommendations based on distributed data has received an increasing amount of attention because it offers several advantages. Online vendors who face problems caused by a limited amount of available data want ... -
Privacy-preserving SOM-based recommendations on horizontally distributed data
Kaleli, Cihan; Polat, Hüseyin (Elsevier Science BV, 2012)To produce predictions with decent accuracy, collaborative filtering algorithms need sufficient data. Due to the nature of online shopping and increasing amount of online vendors, different customers' preferences about the ... -
Privacy-Preserving Svd-Based Collaborative Filtering on Partitioned Data
Yakut, İbrahim; Polat, Hüseyin (World Scientific Publ Co Pte LTD, 2010)Collaborative filtering (CF) systems are widely employed by many e-commerce sites for providing recommendations to their customers. To recruit new customers, retain the current ones, and gain competitive edge over competing ...