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Case recommendation based on fuzzy clustering in personalization web services

2013 3rd International Symposium on Chemical Engineering and Material Properties, ISCEMP 2013

作者： Chen, Xue Gang Zhang, Jia Lu Cheng, Jie Ren Department of Computer science Xiangnan University Chenzhou 423000 China Department of Math Xiangnan University Chenzhou 423000 China College of Applied Science and Technology Hainan University Hainan China

ISBN: (纸本)9783037858363

Aiming at the problems of no strong real-time performance and poor scalability using traditional filtering recommendation technology, and a novel case recommended based on fuzzy clustering is proposed in this paper. Using case-based reasoning technology to personalized recommendation system, and the old case is clustered using fuzzy clustering algorithm, and a classification model is built, and the target case-the case base is converted to the target case-case class to reduce the most case retrieval space of the target case's the nearest neighbors. The experimental results indicate that this method can effectively improve the real-time performance, and it is used in E-commerce recommendation systems, and the degree of recommendation results universe of discourse is improved. © (2013) Trans Tech Publications, Switzerland.

关键词： Fuzzy clustering

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Administration and academic staff performance management system using content management system (CMS) technologies

Administration and academic staff performance management sys...

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International Conference on Electronics, computer and Computation (ICECCO)

作者： Moussa Mahamat Boukar Isa Muslu Department of Computer Science Nigerian Turkish Nile University Abuja Nigeria Department of Applied Math. International Ataturk Alatoo University Bishkek Kyrgyzstan

Content management systems (CMS) provide an optimal solution by organizing information and, mostly, creating and managing an enterprises knowledge. This paper aims to construct an interactive dynamic system base on CMS technologies, on which a range of problems concerning the administration and academic aspects of a university management system can be analyzed and certain policies for overcoming these problems can be tested and improved. This pilot was developed to explore the versatility of content management system (CMS) and to use the technology of CMS as precursor to handle content of a full blown automation of administration and academic performance management system.

关键词： Content management Educational institutions Instruments Information management Automation Companies

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An O(n½+?)-Space and Polynomial-Time Algorithm for Directed Planar Reachability

An O(n½+?)-Space and Polynomial-Time Algorithm for Directed...

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Annual IEEE Conference on Computational Complexity

作者： Tatsuya Imai Kotaro Nakagawa A. Pavan N.V. Vinodchandran Osamu Watanabe Department of Math. and Computer Science Tokyo Institute of Technology Japan Department of Computer Science Iowa State University USA Department of Computer Science and Engineering University of Nebraska-Lincoln USA

We show that the reachability problem over directed planar graphs can be solved simultaneously in polynomial time and approximately O(√n) space. In contrast, the best space bound known for the reachability problem on... 详细信息

关键词： Particle separators Face Polynomials Algorithm design and analysis Complexity theory Standards Silicon

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Limiting spectral distribution of a symmetrized auto-cross covariance matrix

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Annals of applied Probability 2014年第3期24卷 1199-1225页

作者： Jin, Baisuo Wang, Chen Bai, Z.D. Nair, Krishnan Harding, Matthew University of Science and Technology of China National University of Singapore Northeast Normal University and National University of Singapore China Department of Statistics and Finance University of Science and Technology of China Hefei 96 Jinzhai Road China Department of Statistics and Applied Probability National University of Singapore Singapore Klasmoe and School of Math. and Stat Northeast Normal University Changchun 5268 Renmin Street China Department of Civil and Environmental Engineering Stanford University Stanford CA94305 439 Panama Mall United States Department of Economics Stanford University StanfordCA94305 579 Serra Mall United States

This paper studies the limiting spectral distribution (LSD) of a symmetrized auto-cross covariance matrix. The auto-cross covariance matrix is defined as Mτ= 1/2T ∑Tj =1(eje*j+τ +ej+τe*j), where ej is an N dimensi...

This paper studies the limiting spectral distribution (LSD) of a symmetrized auto-cross covariance matrix. The auto-cross covariance matrix is defined as M_τ= 1/2T ∑^T_j ₌₁(e_je^*_j+τ ⁺e_j+τe^*_j), where ej is an N dimensional vectors of independent standard complex components with properties stated in Theorem 1.1, and τ is the lag. M0 is well studied in the literature whose LSD is theMarčenko-Pastur (MP) Law. The contribution of this paper is in determining the LSD of M_τ where τ ≥ 1. It should be noted that the LSD of the M_τ does not depend on τ . This study arose from the investigation of and plays an key role in the model selection of any large dimensional model with a lagged time series structure, which is central to large dimensional factor models and singular spectrum analysis. ©Institute of math.matical Statistics, 2014.

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Calculation of ℌ∞-optimal actuator location for distributed parameter systems

Calculation of ℌ∞-optimal actuator location for distribute...

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American Control Conference (ACC)

作者： Dhanaraja Kasinathan Kirsten Morris Steven Yang Department of Mechl & Mechatronics Engineering (DK) Department of Applied Math. (KM) Department of Elecectrical& Computer Engineering (SY) University of Waterloo Waterloo ONT Canada

In control of distributed parameter systems, there is usually freedom on where to place the actuators. The actuator location should be chosen to optimize the performance objectives and regarded as part of the controller design. In this paper, H ∞ -performance with full information is considered. An algorithm to solve the problem is described and the optimal actuator locations are calculated for several examples.

关键词： Actuators Attenuation Approximation methods Riccati equations math.matical model Distributed parameter systems Cost function

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The δ- sensitivity and its application to stochastic optimal control of nonlinear diffusions.

The δ- sensitivity and its application to stochastic optima...

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American Control Conference

作者： Evangelos A. Theodorou Emo Todorov the Department of Computer Science and Engineering University of Washington Seattle. Departments of Computer Science and Engineering and Applied Math University of Washington

ISBN: (纸本)9781479901777

We provide optimal control laws by using tools from stochastic calculus of variations and the math.matical concept of δ-sensitivity. The analysis relies on logarithmic transformations of the value functions and the use of linearly solvable Partial Differential Equations(PDEs). We derive the corresponding optimal control as a function of the δ-sensitivity of the logarithmic transformation of the value function for the case of nonlinear diffusion processes affine in control and noise.

关键词： nonlinear diffusions PDEs value functions

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PCPs via Low-Degree Long Code and Hardness for Constrained Hypergraph Coloring

PCPs via Low-Degree Long Code and Hardness for Constrained H...

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Annual IEEE Symposium on Foundations of computer science

作者： Irit Dinur Venkatesan Guruswami Dept. of Applied Math and Computer Science The Weizmann Institute of Science Rehovot Israel Computer Science Department Carnegie Mellon University Pittsburgh USA

We develop new techniques to incorporate the recently proposed “short code” (a low-degree version of the long code) into the construction and analysis of PCPs in the classical “Label Cover + Fourier Analysis” framework. As a result, we obtain more size-efficient PCPs that yield improved hardness results for approximating CSPs and certain coloringtype problems. In particular, we show a hardness for a variant of hypergraph coloring (with hyperedges of size 6), with a gap between 2 and exp(2 Ω (√log log N)) number of colors where N is the number of vertices. This is the first hardness result to go beyond the O(log N) barrier for a coloring-type problem. Our hardness bound is a doubly exponential improvement over the previously known O(log log N)-coloring hardness for 2-colorable hypergraphs, and an exponential improvement over the (logN) Ω(1) -coloring hardness for O(1)-colorable hypergraphs. Stated in terms of “covering complexity,” we show that for 6-ary Boolean CSPs, it is hard to decide if a given instance is perfectly satisfiable or if it requires more than 2Ω(√log log N) assignments for covering all of the constraints. While our methods do not yield a result for conventional hypergraph coloring due to some technical reasons, we also prove hardness of (log N) Ω(1) -coloring 2-colorable 6-uniform hypergraphs (this result relies just on the long code). A key algebraic result driving our analysis concerns a very low-soundness error testing method for Reed-Muller codes. We prove that if a function β : F 2 m → F 2 is 2 Ω(d) far in absolute distance from polynomials of degree m-d, then the probability that deg(βg) ≤ m-3d/4 for a random degree d/4 polynomial g is doubly exponentially small in d.

关键词： Frequency modulation Polynomials Color Testing Approximation methods Noise computer science

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Multi-Robot Active SLAM with Relative Entropy Optimization

Multi-Robot Active SLAM with Relative Entropy Optimization

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American Control Conference

作者： Michail Kontitsis Evangelos A. Theodorou Emanuel Todorov Department of Electrical Engineering University of Denver Colorado Department of Computer Science and Engineering University of Washington Seattle Department of Computer Science and Engineering and the Applied Math Department University of Washington Seattle

ISBN: (纸本)9781479901777

This paper presents a new approach for Active Simultaneous Localization and Mapping that uses the Relative Entropy (RE) optimization method to select trajectories which minimize both the localization error and the corresponding uncertainty bounds. To that end we construct a planning cost function which includes, besides the state and control cost, a term that encapsulates the uncertainty of the state. This term is the trace of the state covariance matrix produced by the estimator, in this case an Extended Kalman Filter. The role of the RE method is to iteratively guide the selection of the trajectories towards the ones minimizing the aforementioned cost. Once the method has converged, the result is a near-optimal path in terms of achieving the pre-defined goal in the state space while also improving the localization error and the total uncertainty. In essence the method integrates motion planning with robot localization. To evaluate the approach we consider scenarios with single and multiple robots navigating in presence of obstacles and various conditions of landmark densities. The results show a behavior consistent with our expectations.

关键词： Relative Entropy Optimization SLAM RE

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Free energy based policy gradients

Free energy based policy gradients

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IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning, (ADPRL)

作者： Evangelos A. Theodorou Jiri Najemnik Emo Todorov Department of Computer Science and Engineering University of Washington Seattle University of Washington Seattle Departments of Computer Science and Engineering and Applied Math University of Washington Seattle

Despite the plethora of reinforcement learning algorithms in machine learning and control, the majority of the work in this area relies on discrete time formulations of stochastic dynamics. In this work we present a new policy gradient algorithm for reinforcement learning in continuous state action spaces and continuous time for free energy-like cost functions. The derivation is based on successive application of Girsanov's theorem and the use of the Radon Nikodým derivative as formulated for Markov diffusion processes. The resulting policy gradient is reward weighted. The use of Radon Nikodým extends analysis and results to more general models of stochasticity in which jump diffusions processes are considered. We apply the resulting algorithm in two simple examples for learning attractor landscapes in rhythmic and discrete movements.

关键词： Learning (artificial intelligence) Diffusion processes Markov processes Cost function Equations Heuristic algorithms

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Time Varying Nonlinear Policy Gradients

Time Varying Nonlinear Policy Gradients

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IEEE Annual Conference on Decision and Control

作者： Evangelos A. Theodorou Krishnamurthy Dvijotham Emo Todorov School of Aerospace Engineering Georgia Institute of Technology Atlanta Department of Computer Science and Engineering University of Washington Seattle Departments of Computer Science and Engineering and Applied Math University of Washington Seattle

ISBN: (纸本)9781467357159

We derive Policy Gradients(PGs) with time varying parameterizations for nonlinear diffusion processes affine in noise. The resulting policies have the form of reward weighted gradient. The analysis is in continuous time and includes the case of linear and nonlinear parameterizations. Examples on stochastic control problems for diffusions processes are provided.

关键词： Trajectory Linear programming Noise Diffusion processes Aerodynamics Educational institutions Equations

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