Yazar "Bilge, Alper" için 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. ... -
Design and implementation of a TCP/IP stack for GeekOS operating system
Bilge, Alper (Anadolu Üniversitesi, 2008)GeekOS Maryland Üniversitesi'nde lisans öğrencilerine işletim sistemleri temellerini göstermek üzere tasarlanmış küçük ve basit bir işletim sistemidir. GeekOS 2006 yılında Anadolu Üniversitesi'nde bir bitirme projesi olarak ... -
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 ... -
Filling missing ratings in privacy-preserving collaborative filtering systems
Özcan, Mehmet (Anadolu Üniversitesi, 2018)Ortak filtreleme kullanıcıların değerlemelerini kullanarak benzer kullanıcıları tespit eden ve onlar için tahmin üreten etkili bir kişiye özgü öneri tekniğidir. Fakat bu teknikle ilgili tartışmalı birinci mesele, ciddi ... -
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 Accuracy of Multi-Criteria Collaborative Filtering By Normalizing User Ratings
Bilge, Alper; Yargıç, Alper (2017)Multi-criteria collaborative filtering schemes allow modeling user preferences in a more detailed manner by collecting ratings on various aspects of a product or service. Although preferences are expressed by numerical ... -
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 ... -
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 ... -
Kullanıcı/ürün çiftleri için en iyi öneri algoritmalarının tespit edilmesi/ İsmail Terzi.
Terzi, İsmail (Anadolu Üniversitesi, 2017)İnternetin yaygınlaşması ve iletişim teknolojilerinin gelişmesiyle birlikte İnternet üzerinden sunulan hizmetler artmıştır. Bu artışın sonucunda kullanıcılar incelenmesi ve takip edilmesi gereken çok miktarda bilgi ve ... -
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 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 Multi-Criteria Item-based Collaborative Filtering Framework
Bilge, Alper; Kaleli, Cihan (IEEE, 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 ... -
Naive Bayes sınıflandırıcı tabanlı ikili-veri çoklu-ölçütlü öneri sistemler
Yalçın, Emre (Anadolu Üniversitesi, 2016)Öneri sistemleri, kullanıcıların herhangi bir çabasına ihtiyaç duymadan onların kişisel özelliklerine ve geçmişteki tercihlerine uygun öğeler tavsiye edebilme yeteneğine sahiplerdir. Bazı ürün ve hizmet alımı durumlarında, ... -
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 ...
