Güncel Gönderiler: Makale Koleksiyonu
Toplam kayıt 100, listelenen: 41-60
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A novel probabilistic feature selection method for text classification
(Elsevier Science BV, 2012)High dimensionality of the feature space is one of the most important concerns in text classification problems due to processing time and accuracy considerations. Selection of distinctive features is therefore essential ... -
Text classification using genetic algorithm oriented latent semantic features
(Pergamon-Elsevier Science LTD, 2014)In this paper, genetic algorithm oriented latent semantic features (GALSF) are proposed to obtain better representation of documents in text classification. The proposed approach consists of feature selection and feature ... -
The impact of preprocessing on text classification
(Elsevier Sci LTD, 2014)Preprocessing is one of the key components in a typical text classification framework. This paper aims to extensively examine the impact of preprocessing on text classification in terms of various aspects such as classification ... -
The Impact of Feature Extraction and Selection on SMS Spam Filtering
(Kaunas University Technology, 2013)This paper investigates the impact of several feature extraction and feature selection approaches on filtering of short message service (SMS) spam messages in two different languages, namely Turkish and English. The entire ... -
Privacy-Preserving Inverse Distance Weighted Interpolation
(Springer Heidelberg, 2014)Inverse distance weighted (IDW) interpolation is one of the well-known geo-statistics techniques. On the one hand, one party (server) holding some measurements for specific locations wants to provide predictions; on the ... -
Robustness analysis of multi-criteria collaborative filtering algorithms against shilling attacks
(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 ... -
A Low-Computational Approach on Gaze Estimation With Eye Touch System
(IEEE-Inst Electrical Electronics Engineers Inc, 2014)Among various approaches to eye tracking systems, light-reflection based systems with non-imaging sensors, e.g., photodiodes or phototransistors, are known to have relatively low complexity; yet, they provide moderately ... -
Edge Drawing: A combined real-time edge and segment detector
(Academic Press Inc Elsevier Science, 2012)We present a novel edge segment detection algorithm that runs real-time and produces high quality edge segments, each of which is a linear pixel chain. Unlike traditional edge detectors, which work on the thresholded ... -
Secure seamless peer-to-peer (P2P) UDP communication using IPv4 LSRR option and IPv4+4 addresses
(Pergamon-Elsevier Science LTD, 2009)The current structure of the Internet, with hosts behind network address translation (NAT) boxes, Causes well-known problems for P2P applications. There are several proposals, e.g., STUN, UPnP, MIDCOM, TURN among others, ... -
Enabling peer-to-peer communication for hosts in private address realms using IPv4 LSRR option and IPv4+4 addresses
(Inst Engineering Technology-Iet, 2009)Enabling peer-to-peer (P2P) communication for hosts behind network address translation (NAT) boxes is an important and difficult problem. Existing proposals, for example, UPnP, MIDCOM, TURN, STUN, STUNT, P2PNAT, NATBlaster ... -
A video encoder design combining edge-adaptive lifting and scalable block-matching with motion compensation
(Tubitak Scientific & Technical Research Council Turkey, 2012)This study aimed to achieve video compression by using a novel lifting-based hybrid encoder that also uses motion compensation. The proposed encoder separates video frames into temporal groups, within which certain frames ... -
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 ... -
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. ... -
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 ... -
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 ... -
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 ...
