Yazar "Polat, Hüseyin" için listeleme
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Achieving Optimal Privacy in Trust-Aware Social Recommender Systems
Dokoohaki, Nima; Kaleli, Cihan; Polat, Hüseyin; Matskin, Mihhail (Springer-Verlag Berlin, 2010)Collaborative filtering (CF) recommenders are subject to numerous shortcomings such as centralized processing, vulnerability to shilling attacks, and most important of all privacy. To overcome these obstacles, researchers ... -
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 ... -
Effects of binary similarity measures on collaborative filtering
Şenyürek, Edip (Anadolu Üniversitesi, 2012)İnternet’in popülerliği arttıkça, İnternet üzerinden sanal satıcılar aracılığıyla alışveriş yapmak da artan bir ilgi görmektedir. Müşteriler kendilerine uygun ürünleri satın almak isterler. Diğer bir deyişle, beğenebilecekleri ... -
Effects of Binary Similarity Measures on Top-N Recommendations
Şenyürek, Edip; Polat, Hüseyin (Anadolu Üniversitesi, 2013)Shopping over the Internet through several e-commerce sites is receiving increasing attention. Customers want to purchase those products that they might like without wasting time and/or money. To help their customers, many ... -
Effects of Inconsistently Masked Data Using RPT on CF with Privacy
Polat, Hüseyin; Du, Wenliang (Assoc Computing Machinery, 2007)Randomized perturbation techniques (RPT) are applied to perturb the customers' private data to protect privacy while providing accurate referrals. In the RPT-based collaborative filtering (CF) with privacy schemes, proposed ... -
Effects of inconsistently masked data using RPT on CF with privacy
Polat, Hüseyin; Du, Wenliang (2007)Randomized perturbation techniques (RPT) are applied to perturb the customers' private data to protect privacy while providing accurate referrals. In the RPT-based collaborative filtering (CF) with privacy schemes, proposed ... -
Efficient paillier cryptoprocessor for privacy-preserving data mining
San, İsmail; At, Nuray; Yakut, İbrahim; Polat, Hüseyin (Wiley-Hindawi, 2016)Paillier cryptosystem is extensively utilized as a homomorphic encryption scheme to ensure privacy requirements in many privacy-preserving data mining schemes. However, overall performance of the applications employing ... -
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 ... -
Finding the State Sequence Maximizing P(O, I vertical bar lambda) on Distributed HMMs with Privacy
Renckes, Şahin; Polat, Hüseyin; Oysal, Yusuf (IEEE, 2009)Hidden Markov models (HMMs) are widely used by many applications for forecasting purposes. They are increasingly becoming popular models as part of prediction systems in finance, marketing, bio-informatics, speech recognition, ... -
Finding the state sequence maximizing P(O, I\?) on distributed HMMs with privacy
Renckes, Şahin; Polat, Hüseyin; Oysal, Yusuf (2009)Hidden Markov models (HMMs) are widely used by many applications for forecasting purposes. They are increasingly becoming popular models as part of prediction systems in nance, marketing, bio-informatics, speech recognition, ... -
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 ... -
An Improved Profile-based CF Scheme with Privacy
Bilge, Alper; Polat, Hüseyin (IEEE Computer Soc, 2011)Traditional collaborative filtering (CF) systems widely employing k- nearest neighbor (kNN) algorithms mostly attempt to alleviate the contemporary problem of information overload by generating personalized predictions for ... -
Improving performance of privacy-preserving collaborative filtering schemes
Bilge, Alper (Anadolu Üniversitesi, 2013)Gizliliği koruyan ortak süzgeçleme yöntemleri bireylerin gizliliklerini tehlikeye atmadan yararlı süzgeçleme becerileri ortaya koymaktadır. Ancak bu sistemler doğruluk, ölçeklenebilirlik ve boşluklu veri sorunlarıyla karşı ...
