Search results for: training algorithm.

Authors: Xingping Sheng

Abstract:

Let T and S be a subspace of Cn and Cm, respectively. Then for A ∈ Cm×n satisfied AT ⊕ S = Cm, the generalized inverse A(2) T,S is given by A(2) T,S = (PS⊥APT )†. In this paper, a finite formulae is presented to compute generalized inverse A(2) T,S under the concept of restricted inner product, which defined as < A,B >T,S=< PS⊥APT,B > for the A,B ∈ Cm×n. By this iterative method, when taken the initial matrix X0 = PTA∗PS⊥, the generalized inverse A(2) T,S can be obtained within at most mn iteration steps in absence of roundoff errors. Finally given numerical example is shown that the iterative formulae is quite efficient.

Keywords: Generalized inverse A(2) T, S, Restricted inner product, Iterative method, Orthogonal projection.

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Authors: Narasimham Challa, Jayaram Pradhan

Abstract:

Cryptographic algorithms play a crucial role in the information society by providing protection from unauthorized access to sensitive data. It is clear that information technology will become increasingly pervasive, Hence we can expect the emergence of ubiquitous or pervasive computing, ambient intelligence. These new environments and applications will present new security challenges, and there is no doubt that cryptographic algorithms and protocols will form a part of the solution. The efficiency of a public key cryptosystem is mainly measured in computational overheads, key size and bandwidth. In particular the RSA algorithm is used in many applications for providing the security. Although the security of RSA is beyond doubt, the evolution in computing power has caused a growth in the necessary key length. The fact that most chips on smart cards can-t process key extending 1024 bit shows that there is need for alternative. NTRU is such an alternative and it is a collection of mathematical algorithm based on manipulating lists of very small integers and polynomials. This allows NTRU to high speeds with the use of minimal computing power. NTRU (Nth degree Truncated Polynomial Ring Unit) is the first secure public key cryptosystem not based on factorization or discrete logarithm problem. This means that given sufficient computational resources and time, an adversary, should not be able to break the key. The multi-party communication and requirement of optimal resource utilization necessitated the need for the present day demand of applications that need security enforcement technique .and can be enhanced with high-end computing. This has promoted us to develop high-performance NTRU schemes using approaches such as the use of high-end computing hardware. Peer-to-peer (P2P) or enterprise grids are proven as one of the approaches for developing high-end computing systems. By utilizing them one can improve the performance of NTRU through parallel execution. In this paper we propose and develop an application for NTRU using enterprise grid middleware called Alchemi. An analysis and comparison of its performance for various text files is presented.

Keywords: Alchemi, GridNtru, Ntru, PKCS.

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Authors: Byung Ki Kim, Ho Min Jung, Jae-Bong Yoo, Wan Yeon Lee, Chan Young Park, Young Woong Ko

Abstract:

In this paper, we present a novel approach to location system under indoor environment. The key idea of our work is accurate distance estimation with cricket-based location system using A* algorithm. We also use magnetic sensor for detecting obstacles in indoor environment. Finally, we suggest how this system can be used in various applications such as asset tracking and monitoring.

Keywords: Cricket, Indoor Location Tracking, Mobile Robot, Localization.

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Authors: Tian Baoguang, Liang Chunyan, Chen Nan

Abstract:

In this paper, the nonlinear matrix equation is investigated. Based on the fixed-point theory, the boundary and the existence of the solution with the case r>-δ_i are discussed. An algorithm that avoids matrix inversion with the case -1<-δ_i<0 is proposed.

Keywords: Nonlinear matrix equation, Positive definite solution, The maximal-minimal solution, Iterative method, Free-inversion

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Authors: D. Almazo, C. Rodríguez, M. Toledo

Abstract:

This work presents a methodology for the selection and design of propeller oriented to the experimental verification of theoretical results. The problem of propeller selection and design usually present itself in the following manner: a certain air volume and static pressure are required for a certain system. Once the necessity of fan design on a theoretical basis has been recognized, it is possible to determinate the dimensions for a fan unit so that it will perform in accordance with a certain set of specifications. The same procedures in this work then can be applied in other propeller selection.

Keywords: airfoil, axial flow, blade, fan, hub, mathematical algorithm, propeller design, simulation, wheel.

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Authors: Azmanirah Ab Rahman, Jamil Ahmad, Ruhizan Muhammad Yasin

Abstract:

Rubric is a very important tool for teachers and students for a variety of purposes. Teachers use the rubric for evaluating student work while students use rubrics for self-assessment. Therefore, this paper was emphasized scoring rubric as a scoring tool for teachers in an environment of Competency Based Education and Training (CBET) in Malaysia Vocational College. A total of three teachers in the fields of electrical and electronics engineering were interviewed to identify how the use of rubrics practiced since vocational transformation implemented in 2012. Overall holistic rubric used to determine the performance of students in the skills area.

Keywords: Rubric, Vocational Education.

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Authors: József Valyon, Gábor Horváth

Abstract:

In comparison to the original SVM, which involves a quadratic programming task; LS–SVM simplifies the required computation, but unfortunately the sparseness of standard SVM is lost. Another problem is that LS-SVM is only optimal if the training samples are corrupted by Gaussian noise. In Least Squares SVM (LS–SVM), the nonlinear solution is obtained, by first mapping the input vector to a high dimensional kernel space in a nonlinear fashion, where the solution is calculated from a linear equation set. In this paper a geometric view of the kernel space is introduced, which enables us to develop a new formulation to achieve a sparse and robust estimate.

Keywords: Support Vector Machines, Least Squares SupportVector Machines, Regression, Sparse approximation.

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Authors: Carlos Gonzalez

Abstract:

This paper describes the use of the Internet as a feature to enhance the security of our software that is going to be distributed/sold to users potentially all over the world. By placing in a secure server some of the features of the secure software, we increase the security of such software. The communication between the protected software and the secure server is done by a double lock algorithm. This paper also includes an analysis of intruders and describes possible responses to detect threats.

Keywords: Internet, secure software, threats, cryptography process.

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Authors: Divyesh Patel, Tanuja Srivastava

Abstract:

This paper considers the NP-hard problem of reconstructing binary matrices satisfying exactly-1-4-adjacency constraint from its row and column projections. This problem is formulated into a maximization problem. The objective function gives a measure of adjacency constraint for the binary matrices. The maximization problem is solved by the simulated annealing algorithm and experimental results are presented.

Keywords: Discrete Tomography, exactly-1-4-adjacency, simulated annealing.

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Authors: Michaela Vašková

Abstract:

With the increasing dependence of countries on the critical infrastructure, it increases their vulnerability. Big threat is primarily in the human factor (personnel of the critical infrastructure) and in terrorist attacks. It emphasizes the development of methodology for searching of weak points and their subsequent elimination. This article discusses methods for the analysis of safety in the objects of critical infrastructure. It also contains proposal for methodology for training employees of security services in the objects of the critical infrastructure and developing scenarios of attacks on selected objects of the critical infrastructure.

Keywords: Critical infrastructure, object of critical infrastructure, protection, safety, security, security audit.

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Authors: Jiashang Jiang, Hao Liu, Yongxin Yuan

Abstract:

In this paper the gradient based iterative algorithms are presented to solve the following four types linear matrix equations: (a) AXB = F; (b) AXB = F, CXD = G; (c) AXB = F s. t. X = XT ; (d) AXB+CYD = F, where X and Y are unknown matrices, A,B,C,D, F,G are the given constant matrices. It is proved that if the equation considered has a solution, then the unique minimum norm solution can be obtained by choosing a special kind of initial matrices. The numerical results show that the proposed method is reliable and attractive.

Keywords: Matrix equation, iterative algorithm, parameter estimation, minimum norm solution.

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Authors: Tan Ping Hua, Yeong Che Fai, Ricky Yap, Eileen Su Lee Ming

Abstract:

Haptics has been used extensively in many applications especially in human machine interaction and virtual reality systems. Haptic technology allows user to perceive virtual reality as in real world. However, commercially available haptic devices are expensive and may not be suitable for educational purpose. This paper describes the design and development of a low cost haptic knob, with only one degree of freedom, for use in rehabilitation or training hand pronation and supination. End-effectors can be changed to suit different applications or variation in hand sizes and hand orientation.

Keywords: haptic, microcontroller, real time, virtual reality, rehabilitation

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Authors: Tsuyoshi Okita, Tatsuya Niwa

Abstract:

For a given specific problem an efficient algorithm has been the matter of study. However, an alternative approach orthogonal to this approach comes out, which is called a reduction. In general for a given specific problem this reduction approach studies how to convert an original problem into subproblems. This paper proposes a formal modeling language to support this reduction approach. We show three examples from the wide area of learning problems. The benefit is a fast prototyping of algorithms for a given new problem.

Keywords: Formal language, statistical inference problem, reduction.

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Authors: M. Naserian, M. Jooshaki, M. Fotuhi-Firuzabad, M. Hossein Mohammadi Sanjani, A. Oraee

Abstract:

In recent years, the development of communication infrastructure and smart meters have facilitated the utilization of demand-side resources which can enhance stability and economic efficiency of power systems. Direct load control programs can play an important role in the utilization of demand-side resources in the residential sector. However, investments required for installing control equipment can be a limiting factor in the development of such demand response programs. Thus, selection of consumers with higher potentials is crucial to the success of a direct load control program. Heating, ventilation, and air conditioning (HVAC) systems, which due to the heat capacity of buildings feature relatively high flexibility, make up a major part of household consumption. Considering that the consumption of HVAC systems depends highly on the ambient temperature and bearing in mind the high investments required for control systems enabling direct load control demand response programs, in this paper, a solution is presented to uncover consumers with high air conditioner demand among a large number of consumers and to measure the demand response potential of such consumers. This can pave the way for estimating the investments needed for the implementation of direct load control programs for residential HVAC systems and for estimating the demand response potentials in a distribution system. In doing so, we first cluster consumers into several groups based on the correlation coefficients between hourly consumption data and hourly temperature data using K-means algorithm. Then, by applying a recent algorithm to the hourly consumption and temperature data, consumers with high air conditioner consumption are identified. Finally, demand response potential of such consumers is estimated based on the equivalent desired temperature setpoint changes.

Keywords: Data-driven analysis, demand response, direct load control, HVAC system.

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Authors: Marcel Shirvanian, Wolfram Lippe

Abstract:

Although the usefulness of fuzzy databases has been pointed out in several works, they are not fully developed in numerous domains. A task that is mostly disregarded and which is the topic of this paper is the determination of suitable inequalities for fuzzy sets in fuzzy query languages. This paper examines which kinds of fuzzy inequalities exist at all. Afterwards, different procedures are presented that appear theoretically appropriate. By being applied to various examples, their strengths and weaknesses are revealed. Furthermore, an algorithm for an efficient computation of the selected fuzzy inequality is shown.

Keywords: Fuzzy Databases, Fuzzy Inequalities, Fuzzy QueryLanguages, Fuzzy Ranking.

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Authors: Minghui Wang, Juntao Zhang

Abstract:

An inversion-free iterative algorithm is presented for solving nonlinear matrix equation with a stepsize parameter t. The existence of the maximal solution is discussed in detail, and the method for finding it is proposed. Finally, two numerical examples are reported that show the efficiency of the method.

Keywords: Inversion-free method, Hermitian positive definite solution, Maximal solution, Convergence.

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Authors: Willem Waegeman, Luc Boullart

Abstract:

Instead of traditional (nominal) classification we investigate the subject of ordinal classification or ranking. An enhanced method based on an ensemble of Support Vector Machines (SVM-s) is proposed. Each binary classifier is trained with specific weights for each object in the training data set. Experiments on benchmark datasets and synthetic data indicate that the performance of our approach is comparable to state of the art kernel methods for ordinal regression. The ensemble method, which is straightforward to implement, provides a very good sensitivity-specificity trade-off for the highest and lowest rank.

Keywords: Ordinal regression, support vector machines, ensemblelearning.

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Authors: C. B. Masera, M. Imprialou, L. Budd, C. Morton

Abstract:

Even though signalised intersections are necessary for urban road traffic management, they can act as bottlenecks and disrupt traffic operations. Interrupted traffic flow causes congestion, delays, stop-and-go conditions (i.e. excessive acceleration/deceleration) and longer journey times. Vehicle and infrastructure connectivity offers the potential to provide improved new services with additional functions of assisting drivers. This paper focuses on one of the applications of vehicle-to-infrastructure communication namely Green Light Optimal Speed Advisory (GLOSA). To assess the effectiveness of GLOSA in the urban road network, an integrated microscopic traffic simulation framework is built into VISSIM software. Vehicle movements and vehicle-infrastructure communications are simulated through the interface of External Driver Model. A control algorithm is developed for recommending an optimal speed that is continuously updated in every time step for all vehicles approaching a signal-controlled point. This algorithm allows vehicles to pass a traffic signal without stopping or to minimise stopping times at a red phase. This study is performed with all connected vehicles at 100% penetration rate. Conventional vehicles are also simulated in the same network as a reference. A straight road segment composed of two opposite directions with two traffic lights per lane is studied. The simulation is implemented under 150 vehicles per hour and 200 per hour traffic volume conditions to identify how different traffic densities influence the benefits of GLOSA. The results indicate that traffic flow is improved by the application of GLOSA. According to this study, vehicles passed through the traffic lights more smoothly, and waiting times were reduced by up to 28 seconds. Average delays decreased for the entire network by 86.46% and 83.84% under traffic densities of 150 vehicles per hour per lane and 200 vehicles per hour per lane, respectively.

Keywords: Connected vehicles, GLOSA, intelligent transportation systems, infrastructure-to-vehicle communication.

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Authors: M. Bastanfard, S. Jafari, B.Jalaeian

Abstract:

Ultrasound images are very useful diagnostic tool to distinguish benignant from malignant masses of the breast. However, there is a considerable overlap between benignancy and malignancy in ultrasonic images which makes it difficult to interpret. In this paper, a new noise removal algorithm was used to improve the images and classification process. The masses are classified by wavelet transform's coefficients, morphological and textural features as a novel feature set for this goal. The Bayesian estimation theory is used to classify the tissues in three classes according to their features.

Keywords: Bayesian estimation theory, breast, ultrasound, wavelet.

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Authors: Kaveh Mollazade, Hojat Ahmadi, Mahmoud Omid, Reza Alimardani

Abstract:

Recently, the issue of machine condition monitoring and fault diagnosis as a part of maintenance system became global due to the potential advantages to be gained from reduced maintenance costs, improved productivity and increased machine availability. The aim of this work is to investigate the effectiveness of a new fault diagnosis method based on power spectral density (PSD) of vibration signals in combination with decision trees and fuzzy inference system (FIS). To this end, a series of studies was conducted on an external gear hydraulic pump. After a test under normal condition, a number of different machine defect conditions were introduced for three working levels of pump speed (1000, 1500, and 2000 rpm), corresponding to (i) Journal-bearing with inner face wear (BIFW), (ii) Gear with tooth face wear (GTFW), and (iii) Journal-bearing with inner face wear plus Gear with tooth face wear (B&GW). The features of PSD values of vibration signal were extracted using descriptive statistical parameters. J48 algorithm is used as a feature selection procedure to select pertinent features from data set. The output of J48 algorithm was employed to produce the crisp if-then rule and membership function sets. The structure of FIS classifier was then defined based on the crisp sets. In order to evaluate the proposed PSD-J48-FIS model, the data sets obtained from vibration signals of the pump were used. Results showed that the total classification accuracy for 1000, 1500, and 2000 rpm conditions were 96.42%, 100%, and 96.42% respectively. The results indicate that the combined PSD-J48-FIS model has the potential for fault diagnosis of hydraulic pumps.

Keywords: Power Spectral Density, Machine ConditionMonitoring, Hydraulic Pump, Fuzzy Logic.

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Authors: Yanting Cao, Kazumitsu Nawata

Abstract:

As smartphones are continually upgrading, their software and hardware are getting smarter, so the smartphone-based human activity recognition will be described more refined, complex and detailed. In this context, we analyzed a set of experimental data, obtained by observing and measuring 30 volunteers with six activities of daily living (ADL). Due to the large sample size, especially a 561-feature vector with time and frequency domain variables, cleaning these intractable features and training a proper model become extremely challenging. After a series of feature selection and parameters adjustments, a well-performed SVM classifier has been trained. 

Keywords: smart sensors, human activity recognition, artificial intelligence, SVM

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Authors: B. I. Zhumagaliyev, L. Sh. Balgabayeva, G. S. Nabiyeva, B. A. Tulegenova, P. Oralkhan, B. S. Kalenova, S. S. Akhmetov

Abstract:

The article describes an approach to build competence in research of Bachelor and Master, which is now an important feature of modern specialist in the field of engineering. We provide an example of methodical teaching methods with the research aspect, including the formulation of the problem, the method of conducting experiments, analysis of the results. Implementation of methods allows the student to better consolidate their knowledge and skills at the same time to get research. Knowledge on the part of the media requires some training in the subject area and teaching methods.

Keywords: Professional competence, its model–specialties, teaching methods, educational technology, decision making.

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Authors: Triyanto

Abstract:

Government of Indonesia held a certification program to enhance the professionalism of teachers by using portfolio assessment. This research discusses about the effectiveness of certification programs to enhance the professionalism of teacher in Indonesia. Portfolio assessment method has drawbacks. The certified teachers do not show significant performance improvement. Therefore, the government changes the portfolio assessment method to the education and training for teachers.

Keywords: Profesionalism, Teacher, Certification, Indonesia

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Authors: Chei-Chang Chiou, Sen-Wei Wang, Yu-Min Wang

Abstract:

The purpose of this study is to investigate the relationship between corporate governance and pricing for initial public offerings (IPOs). Empirical result finds that the prediction of pricing of IPOs with corporate governance added can have a rather higher degree of predicting accuracy than that of non governance added during the training and testing samples. Therefore, it can be observed that corporate governance mechanism can affect the pricing of IPOs

Keywords: Artificial neural networks, corporate governance, initial public offerings.

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Authors: Samee Ullah Khan, C. Ardil

Abstract:

Smart Dust particles, are small smart materials used for generating weather maps. We investigate question of the optimal number of Smart Dust particles necessary for generating precise, computationally feasible and cost effective 3–D weather maps. We also give an optimal matching algorithm for the generalized scenario, when there are N Smart Dust particles and M ground receivers.

Keywords: Remote sensing, smart dust, matching, optimization.

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Authors: Gopal Chandra Saha, Sumanta Daw

Abstract:

Warm-up is an essential component for optimizing performance in various sports before a physical fitness training session. This study investigated the immediate comparative effect of Self-Myofascial Release through vibration rolling (VR), non-vibration rolling (NVR), and static stretching as a part of a warm-up treatment on the functional fitness of young adults. Functional fitness is a classification of training that prepares the body for real-life movements and activities. For the present study 20male physical education students were selected as subjects. The age of the subjects was ranged from 20-25 years. The functional fitness variables undertaken in the present study were flexibility, muscle strength, agility, static and dynamic balance of the lower extremity. Each of the three warm-up protocol was administered on consecutive days, i.e. 24 hr time gap and all tests were administered in the morning. The mean and SD were used as descriptive statistics. The significance of statistical differences among the groups was measured by applying ‘F’-test, and to find out the exact location of difference, Post Hoc Test (Least Significant Difference) was applied. It was found from the study that only flexibility showed significant difference among three types of warm-up exercise. The observed result depicted that VR has more impact on myofascial release in flexibility in comparison with NVR and stretching as a part of warm-up exercise as ‘p’ value was less than 0.05. In the present study, within the three means of warm-up exercises, vibration roller showed better mean difference in terms of NVR, and static stretching exercise on functional fitness of young physical education practitioners, although the results were found insignificant in case of muscle strength, agility, static and dynamic balance of the lower extremity. These findings suggest that sports professionals and coaches may take VR into account for designing more efficient and effective pre-performance routine for long term to improve exercise performances. VR has high potential to interpret into an on-field practical application means.

Keywords: Self-myofascial release, functional fitness, foam roller, physical education.

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Authors: Abolfazl Jalilvand, Mohammad Reza Feyzi, Sohrab Khanmohammad, Mohammad Bagher Bana Sharifian, Ali Sajjadi

Abstract:

Nowadays the control of stator voltage at a constant frequency is one of the traditional and low expense methods in order to control the speed of induction motors near its nominal speed. The torque of induction motor is a nonlinear function of the firing angle, phase angle and speed. In this paper the speed control of induction motor regarding various load torque and under different conditions will be investigated based on a fuzzy controller with inverse training.

Keywords: Three phase induction motor, AC converter, speedcontrol, fuzzy control.

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Authors: Teerada Apibunyopas, Nithinant Thammakoranonta

Abstract:

Many organizations bring e-Learning to use as a tool in their training and human development department. It is getting more popular because it is easy to access to get knowledge all the time and also it provides a rich content, which can develop the employees’ skill efficiently. This study is focused on the factors that affect using e-Learning efficiently, so it will make job satisfaction increasing. The questionnaires were sent to employees in large commercial banks, which use e-Learning located in Bangkok, the results from multiple linear regression analysis showed that employee’s characteristics, characteristics of e-Learning, learning and growth have influence on job satisfaction.

Keywords: e-Learning, Job Satisfaction, Learning and growth.

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Authors: Kuo-Lung Wu

Abstract:

The weighting exponent m is called the fuzzifier that can have influence on the clustering performance of fuzzy c-means (FCM) and mÎ[1.5,2.5] is suggested by Pal and Bezdek [13]. In this paper, we will discuss the robust properties of FCM and show that the parameter m will have influence on the robustness of FCM. According to our analysis, we find that a large m value will make FCM more robust to noise and outliers. However, if m is larger than the theoretical upper bound proposed by Yu et al. [14], the sample mean will become the unique optimizer. Here, we suggest to implement the FCM algorithm with mÎ[1.5,4] under the restriction when m is smaller than the theoretical upper bound.

Keywords: Fuzzy c-means, robust, fuzzifier.

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Authors: Francisco Echarte, José Javier Astrain, Alberto Córdoba, Jesús Villadangos

Abstract:

Ontologies and tagging systems are two different ways to organize the knowledge present in the current Web. In this paper we propose a simple method to model folksonomies, as tagging systems, with ontologies. We show the scalability of the method using real data sets. The modeling method is composed of a generic ontology that represents any folksonomy and an algorithm to transform the information contained in folksonomies to the generic ontology. The method allows representing folksonomies at any instant of time.

Keywords: Folksonomies, ontologies, OWL, semantic web.

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