Kurum Yazarı "Kaleli, Cihan" Scopus İndeksli Yayınlar Koleksiyonu İçin 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 ... -
An entropy-based neighbor selection approach for collaborative filtering
Kaleli, Cihan (Elsevier, 2014)Collaborative filtering is an emerging technology to deal with information overload problem guiding customers by offering recommendations on products of possible interest. Forming neighborhood of a user/item is the crucial ... -
Methods of Privacy Preserving in Collaborative Filtering
Batmaz, Zeynep; Kaleli, Cihan (IEEE, 2017)Privacy considerations of individuals becomes more and more popular issue in recommender systems due to the increasing need for protecting confidential data. Even though users of recommender systems enjoy with personalized ... -
A multi-criteria item-based collaborative filtering framework
Bilge, Alper; Kaleli, Cihan (IEEE Computer Society, 2014)Collaborative filtering methods are utilized to provide personalized recommendations for users in order to alleviate information overload problem in different domains. Traditional collaborative filtering methods operate ... -
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, ... -
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-Aware Detection of Shilling Profiles on Arbitrarily Distributed Recommender Systems
Yılmazel, Burcu; Bilge, Alper; Kaleli, Cihan (IEEE-Inst Electrical Electronics Engineers Inc, 2019)Due to the mutual advantage of small-scale online service providers, they need to collaborate to deliver recommendations based on arbitrarily distributed preference data without jeopardizing their confidentiality. Besides ... -
Privacy-Preserving Concordance-based Recommendations on Vertically Distributed Data
Kaleli, Cihan (IEEE, 2012)Recommender systems are attractive components of e-commerce. Customers apply such systems to get help for choosing the appropriate product to purchase. To provide accurate and dependable referrals, recommender systems ... -
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 Trust-based Recommendations on Vertically Distributed Data
Kaleli, Cihan; Polat, Hüseyin (IEEE Computer Soc, 2011)Providing recommendations on trusts between entities is receiving increasing attention lately. Customers may prefer different online vendors for shopping. Thus, their preferences about various products might be distributed ... -
Providing naïve Bayesian classifier-based private recommendations on partitioned data
Kaleli, Cihan; Polat, Hüseyin (2007)Data collected for collaborative filtering (CF) purposes might be split between various parties. Integrating such data is helpful for both e-companies and customers due to mutual advantageous. However, due to privacy ... -
Providing Private Recommendations on Personal Social Networks
Kaleli, Cihan; Polat, Hüseyin (Springer-Verlag Berlin, 2010)Personal social networks are recently used to offer recommendations. Due to privacy concerns, privacy protection while generating accurate referrals is imperative. Since accuracy and privacy are conflicting goals, providing ... -
Providing private recommendations using naive Bayesian classifier
Kaleli, Cihan; Polat, Hüseyin (Springer-Verlag Berlin, 2007)Today's CF systems fail to protect users' privacy. Without privacy protection, it becomes a challenge to collect sufficient and high quality data for CF. With privacy protection, users feel comfortable to provide more ... -
A review on deep learning for recommender systems: challenges and remedies
Batmaz, Zeynep; Yürekli, Ali; Bilge, Alper; Kaleli, Cihan (Springer, 2019)Recommender systems are effective tools of information filtering that are prevalent due to increasing access to the Internet, personalization trends, and changing habits of computer users. Although existing recommender ... -
Robustness analysis of arbitrarily distributed data-based recommendation methods
Yılmazel, Burcu Yurekli; Kaleli, Cihan (Pergamon-Elsevier Science LTD, 2016)Due to different shopping routines of people, rating preferences of many customers might be partitioned between two parties. Since two different e-companies might sell products from the same range to the identical set of ... -
Robustness analysis of naïve Bayesian classifier-based collaborative filtering
Kaleli, Cihan; Polat, Hüseyin (Springer Verlag, 2013)In this study, binary forms of previously defined basic shilling attack models are proposed and the robustness of naïve Bayesian classifierbased collaborative filtering algorithm is examined. Real data-based experiments ... -
Shilling attacks against recommender systems: a comprehensive survey
Güneş, İhsan; Kaleli, Cihan; Bilge, Alper; Polat, Hüseyin (Springer, 2014)Online vendors employ collaborative filtering algorithms to provide recommendations to their customers so that they can increase their sales and profits. Although recommendation schemes are successful in e-commerce sites, ... -
Similar or Dissimilar Users? Or Both?
Kaleli, Cihan; Polat, Hüseyin (IEEE Computer Soc, 2009)E-commerce sites utilize collaborative filtering (CF) techniques to offer recommendations to their customers. To recruit new customers and keep the current ones, it is imperative for online vendors to provide accurate ...