Yazar "Polat, Hüseyin" için WoS İndeksli Yayınlar Koleksiyonu 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 ... -
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 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 ... -
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 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, ... -
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 ... -
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 ... -
A novel shilling attack detection method
Bilge, Alper; Özdemir, Zeynep; Polat, Hüseyin (Elsevier Science BV, 2014)Recommender systems provide an impressive way to overcome information overload problem. However, they are vulnerable to profile injection or shilling attacks. Malicious users and/or parties might construct fake profiles ... -
On Binary Similarity Measures for Privacy-Preserving Top-N Recommendations
Bilge, Alper; Kaleli, Cihan; Polat, Hüseyin (Scitepress, 2010)Collaborative filtering (CF) algorithms fundamentally depend on similarities between users and/or items to predict individual preferences. There are various binary similarity measures like Kulzinslcy, Sokal-Michener, Yule, ... -
On the Discovery of Fake Binary Ratings
Okkalıoğlu, Murat; Koç, Mehmet; Polat, Hüseyin (Assoc Computing Machinery, 2015)Privacy-preserving collaborative filtering methods promise to preserve privacy of individuals. In general, privacy has two aspects, preserving the rating values of users and masking who rated which items. In this study, ... -
On the Privacy of Horizontally Partitioned Binary Data-Based Privacy-Preserving Collaborative Filtering
Okkalıoğlu, Murat; Koç, Mehmet; Polat, Hüseyin (Springer Int Publishing Ag, 2016)Collaborative filtering systems provide recommendations for their users. Privacy is not a primary concern in these systems; however, it is an important element for the true user participation. Privacy-preserving collaborative ... -
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, ... -
Pcf: Projection-Based Collaborative Filtering
Yakut, İbrahim; Polat, Hüseyin; Koç, Mehmet (Scitepress, 2010)Collaborative filtering (CF) systems are effective solutions for information overload problem while contributing web personalization. Different memory-based algorithms operating over entire data set have been utilized for ...