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Due to the rapid increase in the number of users owning location-based devices, there is a considerable amount of geo-tagged data available on social media websites, such as Twitter and Facebook. This geo-tagged data can be useful in a variety of ways to extract location-specific information, as well as to comprehend the variation of information across different geographical regions. A lot of techniques...
In this study, a two-stage method which extracts fuzzy rules directly from samples is proposed for classification. First, we introduce a neighborhood based attribute significance algorithm to select r of the most important attributes from the original attribute set. Second, the proposed algorithm generates fuzzy rule from each sample described by the selected attribute subset and finally simplifies...
Botnets are networks of compromised computers controlled under a common command and control channel. Recognized as one of the most serious security threats on current Internet infrastructure, botnets are often hidden in existing applications, e.g. IRC, HTTP, or peer-to-peer, which makes botnet detection a challenging problem. In this paper we propose a new, centralized, fully-encrypted, botnet system...
During past decades, land use and land cover change detection techniques have undergone substantial development. However, different scenarios and an integrated workflow linking remote sensing imagery and GIS are often neglected. As a result, we develop a land use and land cover change detection and extraction system and propose five scenarios considering data availability and different classification...
Case based reasoning (CBR) is very important task in data mining, but privacy information will be disclosed easily in CBR. This paper presents random locally linear embedding (LLE) on encrypted case based reasoning method. In order to be ensure the security of the CBR, the parameters nearest neighbor number k and embedded space dimension d of LLE algorithm are selected randomly. Further we embed the...
Protecting Privacy has attracted more and more attention in data mining. Case based reasoning(CBR) is very important task in data mining. This paper presents method that protects the privacy by disordered principal component analysis(PCA) on one class data. In order to be ensure the security of the CBR, we first disorder the PCA to select the principal component confusedly. Further we transform the...
Given a set of lists, where items of each list are sorted by the ascending order of their values, the objective of this paper is to figure out the common items that appear in all of the lists efficiently. This problem is sometimes known as common items extraction from sorted lists. To solve this problem, one common approach is to scan all items of all lists sequentially in parallel until one of the...
Abstract-Traditional EA concepts in the Enterprise Application Integration (EAI) domain focus on ex-post integration of application interfaces by pipelining different middleware technologies like message queuing or remote method invocations [1, 2]. Web Service enabled Service-Oriented Architectures (SOAs) used in the EAI context were a step towards providing an abstraction layer for the involved interfaces...
A privacy preserving classification algorithm based on random Multidimensional Scales (MDS) is presented in this paper. We first alter the selection of the parameter embedded dimension d for satisfying the security of privacy preserving classification. Further the sensitive attributes are embedded into random (even higher) dimension feature space using random MDS algorithm, thus the sensitive attributes...
The Transient Chaotic Neural Network (TCNN) and the Noisy Chaotic Neural Network (NCNN) have been proved their searching abilities for solving combinatorial optimization problems(COPs). The chaotic dynamics of the TCNN and the NCNN are believed to be important for their searching abilities. However, in this paper, we propose a strategy which cuts off the rich dynamics such as periodic and chaotic...
Based on TCP protocol, this paper aims at TCP flows, discusses the effects of multivariate correlation analysis on network traffic, obtains the quantitative relationship between different types of TCP packets in each time unit by correlation coefficient matrix, and finally proposes an anomaly detection and analysis method based on the correlation coefficient matrix. The experimental results show that...
Using the eye-gaze distinguishing and tracking method based on the image processing technique, Hough Transform for detecting circle-center is used to obtain the pupil center's position and to determine the eye-gaze direction, and then horizontal angle and vertical angle of the eyeball rotation is deduced, finally, the tracking of eye-gaze direction is realized. If eye tracking technology has been...
Gabor feature based classification approaches are widely used in face recognition, because they are insensitive to changes in illumination and facial expression. However, most of strategies only use the magnitude of the Gabor wavelet representation of images to generate feature vectors. When only single training image per person is available, the performance of these methods may be limited. In this...
During the last decade, anomaly detection has attracted the attention of many researchers to overcome the weakness of signature-based IDSs in detecting novel attacks, and KDDCUP'99 is the mostly widely used data set for the evaluation of these systems. Having conducted a statistical analysis on this data set, we found two important issues which highly affects the performance of evaluated systems,...
This paper presents nearest neighbor tour circuit encryption algorithm based random Laplacian Eigenmap. In order to be suited for privacy-p reserving classification, we first alter the selection fashion of the parameters nearest neighbor number k, embedded space dimension d and heat kernel factor t of Laplacian Eigenmap algorithm. Further we embed the tourists' sensitive attribution into random dimension...
The recently reported v planning algorithm is modified to handle on-the-fly dynamic updates to the obstacle map. The modified algorithm called All-Pair-Dynamic-Planning(APDP), models the problem of robot path planning in the framework of finite state probabilistic automata and solves the all-pair planning problem in one setting. We use the concept of renormalized measure of regular languages to plan...
We study the problem of reconstructing a sparse signal from a limited number of its linear projections when a part of its support is known. This may be available from prior knowledge. Alternatively, in a problem of recursively reconstructing time sequences of sparse spatial signals, one may use the support estimate from the previous time instant as the ldquoknownrdquo part of the support. The idea...
Reuse of proven process models increases modeling efficiency and ensure the quality of process models. To provide a better support for reuse, the retrieval mechanisms of process repositories should be able to propose similar process models that ranked according to their similarity degrees to the query request. As a process model and a query request on process structure can both be viewed as rooted,...
Summary form only given. Online classification of network traffic is very challenging and still an issue to be solved due to the increase of new applications and traffic encryption. In this paper, we propose a hybrid mechanism for online classification of network traffic, in which we apply a signature-based method at the first level, and then we take advantage of a learning algorithm to classify the...
Customer retention is one of the most important topics in customer relationship management research. To date,customer retention studies are mainly carried out on the macro or firm level instead of the individual customer level. This study develops a model of customer retention management from the individual customer perspective. This model introduces multiple agents and considers the interactions...
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