Kurum Yazarı "Bilge, Alper" Scopus İndeksli Yayınlar Koleksiyonu İçin Listeleme
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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. ... -
The estimation of daily temperature by artificial and fuzzy neural network methods
Bilge, Alper (2007)In this study, the estimation of daily temperature of a region by fuzzy logic is discussed and some results are presented. Temperature is an atmospheric parameter which can be estimated by means of some other atmospheric ... -
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 privacy-preserving NBC-based recommendations by preprocessing
Bilge, Alper; Polat, Hüseyin (2010)Providing accurate predictions efficiently with privacy is imperative for both customers and e-commerce vendors. However, privacy, accuracy, and performance are conflicting goals. Although producing referrals with privacy ... -
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 ... -
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, ... -
Privacy Risks for Multi-Criteria Collaborative Filtering Systems
Yargic, Alper; Bilge, Alper (IEEE, 2017)In case that individuals feel their privacy is violated while using any recommender system, they might be willing to declare incorrect information or even completely refuse to use such services. To relieve customer concerns, ... -
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 multi-criteria collaborative filtering
Yargic, Alper; Bilge, Alper (Elsevier Sci LTD, 2019)Privacy-preserving collaborative filtering schemes focus on eliminating the privacy threats inherent in single preference values, and the privacy risks in the multi-criteria preference domain are disregarded. In this work, ... -
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 ... -
A Robust Multi-Criteria Collaborative Filtering Algorithm
Türk, Ahmet Murat; Bilge, Alper (IEEE, 2018)Collaborative filtering recommender systems assist individuals to discover relevant products or services that they might be interested in a large set of alternatives by analyzing the collected preferences. Recent research ... -
Robustness analysis of multi-criteria collaborative filtering algorithms against shilling attacks
Türk, Ahmet Murat; Bilge, Alper (Pergamon-Elsevier Science LTD, 2019)Collaborative filtering is an emerging recommender system technique that aims guiding users based on other customers preferences with behavioral similarities. Such correspondences are located based on preference history ... -
Robustness analysis of privacy-preserving model-based recommendation schemes
Bilge, Alper; Güneş, İhsan; Polat, Hüseyin (Pergamon-Elsevier Science LTD, 2014)Privacy-preserving model-based recommendation methods are preferable over privacy-preserving memory-based schemes due to their online efficiency. Model-based prediction algorithms without privacy concerns have been ... -
A scalable privacy-preserving recommendation scheme via bisecting k-means clustering
Bilge, Alper; Polat, Hüseyin (Elsevier Sci LTD, 2013)Privacy-preserving collaborative filtering is an emerging web-adaptation tool to cope with information overload problem without jeopardizing individuals' privacy. However, collaborative filtering with privacy schemes ... -
Shilling Attacks Against Memory-Based Privacy-Preserving Recommendation Algorithms
Güneş, İhsan; Bilge, Alper; Polat, Hüseyin (Ksii-Kor Soc Internet Information, 2013)Privacy-preserving collaborative filtering schemes are becoming increasingly popular because they handle the information overload problem without jeopardizing privacy. However, they may be susceptible to shilling or profile ... -
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, ... -
A Survey of Privacy-Preserving Collaborative Filtering Schemes
Bilge, Alper; Kaleli, Cihan; Yakut, İbrahim; Güneş, İhsan; Polat, Hüseyin (World Scientific Publ Co Pte LTD, 2013)With increasing need for preserving confidential data while providing recommendations, privacy-preserving collaborative filtering has been receiving increasing attention. To make data owners feel more comfortable while ...