Güncel Gönderiler: Bilgisayar Mühendisliği Bölümü
Toplam kayıt 216, listelenen: 121-140
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Parallel Matrix Multiplication for Various Implementations
(IEEE, 2013)It has become increasingly common to see that supercomputing applications harness the massive parallelism of graphics cards to speed up computations. In this study, an analysis concerning to the time necessity for four ... -
A 3D Lifting Based Motion Compensation Augmented Video Coder
(IEEE, 2009)This study introduces a video compression method that uses spatio - temporal lifting based algorithms to compress the video signals. The temporal correlation of consecutive frames causes temporal redundancies, which are ... -
A new hybrid recommendation algorithm with privacy
(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 ... -
Providing predictions on distributed HMMs with privacy
(Springer, 2007)As forecasting is increasingly becoming important, hidden Markov models (HMMs) are widely used for prediction in many applications such as finance, marketing, bioinformatics, speech recognition, and so on. After creating ... -
Finding the State Sequence Maximizing P(O, I vertical bar lambda) on Distributed HMMs with Privacy
(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, ... -
A survey: deriving private information from perturbed data
(Springer, 2015)Privacy-preserving data mining has attracted the attention of a large number of researchers. Many data perturbation methods have been proposed to ensure individual privacy. Such methods seem to be successful in providing ... -
Deriving private data in partitioned data-based privacy-preserving collaborative filtering systems
(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. ... -
On the Privacy of Horizontally Partitioned Binary Data-Based Privacy-Preserving Collaborative Filtering
(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 ... -
A Parallel Huffman Coder on the CUDA Architecture
(IEEE, 2014)We present a parallel implementation of the widely-used entropy encoding algorithm, the Huffman coder, on the NVIDIA CUDA architecture. After constructing the Huffman codeword tree serially, we proceed in parallel by ... -
Reconstructing rated items from perturbed data
(Elsevier Science BV, 2016)The basic idea behind privacy-preserving collaborative filtering schemes is to prevent data collectors from deriving the actual rating values and the rated items. Different data perturbation methods have been proposed to ... -
On the Discovery of Fake Binary Ratings
(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, ... -
Privacy-Preserving Kriging Interpolation on Distributed Data
(Springer-Verlag Berlin, 2014)Kriging is one of the most preferred geostatistical methods in many engineering fields. Basically, it creates a model using statistical properties of all measured points in the region, where a prediction value is sought. ... -
Privacy-preserving top-N recommendation on distributed data
(Wiley, 2008)Traditional collaborative filtering (CF) systems perform filtering tasks on existing databases; however, data collected for recommendation purposes may split between different online vendors. To generate better predictions, ... -
Privacy-preserving kriging interpolation on partitioned data
(Elsevier Science BV, 2014)Kriging is well-known, frequently applied method in geo-statistics. Its success primarily depends on the total number of measurements for some sample points. If there are sufficient sample points with measurements, kriging ... -
Effects of Inconsistently Masked Data Using RPT on CF with Privacy
(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 ... -
Private predictions on hidden Markov models
(Springer, 2010)Hidden Markov models (HMMs) are widely used in practice to make predictions. They are becoming increasingly popular models as part of prediction systems in finance, marketing, bio-informatics, speech recognition, signal ... -
SOM-based recommendations with privacy on multi-party vertically distributed data
(Palgrave Macmillan LTD, 2012)Data collected for providing recommendations can be partitioned among different parties. Offering distributed data-based predictions is popular due to mutual advantages. It is almost impossible to present trustworthy ... -
On classification of abstracts obtained from medical journals
(SAGE Publications LTD, 2019)Classification of medical documents was mostly carried out on English data sets and these studies were performed on hospital records rather than academic texts. The main reasons behind this situation are the lack of publicly ... -
Classification of Medical Documents According to Diseases
(IEEE, 2015)Medical text classification is still one of the popular research problems inside text classification domain. Apart from some text data compiled from hospital records, most of the researchers in this field evaluate their ... -
From existing trends to future trends in privacy-preserving collaborative filtering
(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, ...
