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IEEE International Conference on Fuzzy systems (FUZZ-IEEE)

作者： Soheila Ashkezari-T Mohammad-R. Akbarzadeh-T Department of Computer Engineering Cognitive Computing Laboratory Center of Applied Research on Soft computing and Intelligent systems Ferdowsi University of Mashhad Mashhad Iran Departments of Electrical Engineering and Computer Engineering Cognitive Computing Laboratory Center of Applied Research on Soft computing and Intelligent systems Ferdowsi University of Mashhad Iran

The World Wide Web has created a new media for mass marketing that can also be highly customized to online customers' needs and expectations. Recommender systems (RS) play an important role in this area. Here, we aim to establish a genre-based collaborative RS to automatically suggest and rank a list of appropriate items (movies) to a user based on the user profile and the past voting patterns of other users with similar tastes. The contribution of this paper is using genre based information in a hybrid fuzzy-Bayesian network collaborative RS. The interest to the different genres is computed based on a hybrid user model. The similarity of like-minded users according to the fuzzy distance and also Pearson correlation coefficient is involved in a Bayesian network.

关键词： Motion pictures Mathematical model Collaboration Recommender systems Equations Computational modeling

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News filtering and summarization on the Web

News filtering and summarization on the Web

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作者： Wu, Xindong Wu, Gong-Qing Xie, Fei Zhu, Zhu Hu, Xue-Gang Lu, Hao Li, Huiqian School of Computer Science and Information Engineering Hefei University of Technology China Zhejiang Taobao Network China Key Laboratory of Complex Systems and Intelligence Science Institute of Automation Chinese Academy of Sciences China Center for Social Computing and Parallel Systems Institute of Automation Chinese Academy of Sciences China

The news filtering and summarization (NFAS) system can automatically recognize Web news pages, retrieve each news page's title and news content, and extract key phrases. This extraction method substantially outper...

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A comparative study on two large-scale hierarchical text classification tasks' solutions

A comparative study on two large-scale hierarchical text cla...

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International Conference on Machine Learning and Cybernetics

作者： Zhang, Jian Zhao, Hai Lu, Bao-Liang Department of Computer Science and Engineering Center for Brain-Like Computing and Machine Intelligence Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dong Chuan Road Shanghai 200240 China

ISBN: (纸本)9781424465262

Patent classification is a large scale hierarchical text classification (LSHTC) task. Though comprehensive comparisons, either learning algorithms or feature selection strategies, have been fully made in the text categorization field, few work was done for a LSHTC task due to high computational cost and complicated structural label characteristics. For the first time, this paper compares two popular learning frameworks, namely hierarchical support vector machine (SVM) and k nearest neighbor (k-NN) that are applied to a LSHTC task. Experiment results show that the latter outperforms the former in this LSHTC task, which is quite different from the usual results for normal text categorization tasks. Then this paper does a comparative study on different similarity measures and ranking approaches in k-NN framework for LSHTC task. Conclusions can be drawn that k-NN is more appropriate for the LSHTC task than hierarchical SVM and for a specific LSHTC task. BM25 outperforms other similarity measures and List Weak gains a better performance than other ranking approaches. We also find an interesting phenomenon that using all the labels of the retrieved neighbors can remarkably improve classification performance over only using the first label of the retrieved neighbors. © 2010 IEEE.

关键词： Learning algorithms

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Studying the impact of synchronization frequency on scheduling tasks with dependencies in heterogeneous systems

Studying the impact of synchronization frequency on scheduli...

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作者： Andronikos, Theodore Ciorba, Florina M. Riakiotakis, Ioannis Papakonstantinou, George Chronopoulos, Anthony T. Department of Informatics Ionian University Corfu Greece Computing Systems Laboratory Department of Electrical and Computer Engineering National Technical University of Athens Greece Center for Advanced Vehicular Systems Mississippi State University MS United States Department of Computer Science University of Texas at San Antonio 6900 N. Loop 1604 West San Antonio TX 78249 United States

In this work, we develop and evaluate a theoretical model, which we then use to study the impact of the synchronization frequency on the performance of dynamic self-scheduling algorithms. These algorithms are used to parallelize loops with data dependencies on heterogeneous systems. The proposed model uses a formula to estimate the parallel time as a function of the synchronization frequency. Inter-node communication has been proven to be the dominant factor for the performance degradation of applications containing loops with data dependencies. The synchronization mechanism therefore requires careful fine-tuning in order to give the best possible performance. The proposed model determines the optimal synchronization frequency that results in the minimum parallel time. We use this model to study the impact of the synchronization frequency on the parallel execution of a computational kernel from image processing. For this kernel, the synchronization frequency giving the minimum parallel time predicted by our theoretical model was very close to the synchronization frequency giving the least parallel time in practice. We validate our model by extensive comparisons of the theoretically predicted parallel time and synchronization frequency against those obtained from practical experiments. The comparisons show that the proposed model is highly accurate, its predictions for the optimal synchronization frequency being within 0.0250% of the experimentally optimal synchronization frequency in the best case, and within 0.1750% of the experimentally optimal synchronization frequency in the worst case. Finally, the comparisons show that the proposed model improves on a previously existing model in heterogeneous systems, whereas it gives similar results in homogeneous systems. © 2010 Elsevier B.V. All rights reserved.

关键词： Synchronization

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An Empirical Study on Development Set Selection Strategy for Machine Translation Learning∗ 5

An Empirical Study on Development Set Selection Strategy for...

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Joint 5th Workshop on Statistical Machine Translation and MetricsMATR, WMT 2010 at the 48th Conference of the Associationfor Computational Linguistics, ACL 2010

作者： Hui, Cong Zhao, Hai Song, Yan Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dong Chuan Rd. Shanghai 200240 China Department of Chinese Translation and Linguistics City University of Hong Kong Hong Kong

ISBN: (纸本)9781932432718

This paper describes a statistical machine translation system for our participation for the WMT10 shared task. Based on MOSES, our system is capable of translating German, French and Spanish into English. Our main contribution in this work is about effective parameter tuning. We discover that there is a significant performance gap as different development sets are adopted. Finally, ten groups of development sets are used to optimize the model weights, and this does help us obtain a stable evaluation result. © 2010 Association for Computational Linguistics

关键词： Machine translation

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Watershed-based weighted graph partitioning active contours

Watershed-based weighted graph partitioning active contours

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Congress on Image and Signal Processing, CISP

作者： Shaorong Wang Yisong Chen Sheng Li Guoping Wang Hua Li HCI & Multimedia Laboratory of Department of Computer Science Peking University Beijing China National Research Center for Intelligent Computing Systems Institute of Computing Technology Chinese Academy and Sciences Beijing China

A novel Weighted Graph Partitioning Active Contours method based on weighted dissimilarity is introduced. This method is easy to be extended by defining different types of similarities. And it has been greatly acceler... 详细信息

关键词： Image segmentation Active contours Pixel Cost function Minimization Level set Mathematical model

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Online detection of utility cloud anomalies using metric distributions

Online detection of utility cloud anomalies using metric dis...

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IEEE Symposium on Network Operations and Management

作者： Chengwei Wang Vanish Talwar Karsten Schwan Parthasarathy Ranganathan Center for Experimental Research in Computer Systems College of Computing Georgia Institute of Technology Atlanta GA USA HP Laboratory Palo Alto CA USA

ISBN: (纸本)9781424453665;9781424453672

The online detection of anomalies is a vital element of operations in data centers and in utility clouds like Amazon EC2. Given ever-increasing data center sizes coupled with the complexities of systems software, applications, and workload patterns, such anomaly detection must operate automatically, at runtime, and without the need for prior knowledge about normal or anomalous behaviors. Further, detection should function for different levels of abstraction like hardware and software, and for the multiple metrics used in cloud computing systems. This paper proposes EbAT - Entropy-based Anomaly Testing - offering novel methods that detect anomalies by analyzing for arbitrary metrics their distributions rather than individual metric thresholds. Entropy is used as a measurement that captures the degree of dispersal or concentration of such distributions, aggregating raw metric data across the cloud stack to form entropy time series. For scalability, such time series can then be combined hierarchically and across multiple cloud subsystems. Experimental results on utility cloud scenarios demonstrate the viability of the approach. EbAT outperforms threshold-based methods with on average 57.4% improvement in accuracy of anomaly detection and also does better by 59.3% on average in false alarm rate with a `near-optimum' threshold-based method.

关键词： Entropy System software Application software Runtime Hardware Cloud computing Testing Time measurement Dispersion Scalability

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Hedge detection and scope finding by sequence labeling with normalized feature selection

CoNLL-2010: Shared Task - Fourteenth Conference on Computat...

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CoNLL-2010: Shared Task - Fourteenth Conference on Computational Natural Language Learning, Proceedings of the Shared Task 2010年 92-99页

作者： Zhang, Shaodian Zhao, Hai Zhou, Guodong Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Dept of Computer Science and Engineering Shanghai Jiao Tong University China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University China School of Computer Science and Technology Soochow University China

This paper presents a system which adopts a standard sequence labeling technique for hedge detection and scope finding. For the first task, hedge detection, we formulate it as a hedge labeling problem, while for the second task, we use a two-step labeling strategy, one for hedge cue labeling and the other for scope finding. In particular, various kinds of syntactic features are systemically exploited and effectively integrated using a large-scale normalized feature selection method. Evaluation on the CoNLL-2010 shared task shows that our system achieves stable and competitive results for all the closed tasks. Furthermore, post-deadline experiments show that the performance can be much further improved using a sufficient feature selection. © 2010 Association for Computational Linguistics.

关键词： Feature Selection

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A comparative study on two large-scale hierarchical text classification tasks' solutions

A comparative study on two large-scale hierarchical text cla...

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International Conference on Machine Learning and Cybernetics (ICMLC)

作者： Jian Zhang Hai Zhao Bao-Liang Lu Center of Brain-Like Computing and Machine Intelligence(ÇïêDepartment of Computer Science and Engineering Shanghai Jiaotong University Shanghai China MOE-Microsoft Key Laboratory of Intelligent Computing and Intelligent Systems Shanghai Jiaotong University Shanghai China

关键词： Patents Support vector machines Text categorization Nearest neighbor searches Training Classification algorithms Taxonomy

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A Smart-NIC-Based Power-Proxy Solution for Reduced Power Consumption during Instant Messaging

A Smart-NIC-Based Power-Proxy Solution for Reduced Power Con...

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IEEE Green Technologies Conference (IEEE-Green)

作者： Dexiang Wang Janise McNair Alan George Wireless and Mobile Systems Laboratory Department of Electrical and Computer Engineering University of Florida Gainesville USA NSF Center for High-Performance Reconfigurable Computing (CHREC) Department of Electrical and Computer Engineering University of Florida Gainesville USA

ISBN: (纸本)9781424452743

The major challenge to achieving efficient power management for local computers that serve as edge devices of the Internet is to achieve long sleeping times while at the same time maintaining network connectivity. By modifying the network interface card (NIC) with a low-weight proxy module that can handle a certain amount of network protocol semantics and hence still keep the local computer alive on the Internet, a longer host sleeping time can be achieved, while keeping many of the components, including CPU, memory, motherboard, hard drive, etc, remain in a very-low-energy mode. In this paper, we pursue a power-proxy solution to the widely-used Instant Messenger (IM) applications. Yahoo! ® Messenger is selected for a case study to investigate its communication protocol YMSG. Furthermore, the decision on inactivity time-out values is a crucial factor for energy savings, but the random nature of idle periods makes the decision another challenge. We formulate the decision problem into a stochastic program and propose an adaptive algorithm to set up appropriate inactivity time-out values. Simulations show that the proposed power-proxy solution combined with the inactivity time-out setup algorithm can efficiently reduce the power consumption of an edge computer.

关键词： Energy consumption computer networks IP networks Protocols computer network management Energy management Network interfaces computer interfaces Central Processing Unit Drives

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