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An effective data locality aware task scheduling method for MapReduce framework in heterogeneous environments

An effective data locality aware task scheduling method for ...

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2011 International Conference on Cloud and Service computing, CSC 2011

作者： Zhang, Xiaohong Feng, Yuhong Feng, Shengzhong Fan, Jianping Ming, Zhong School of Computer Science and Technology Henan Polytechnic University Jiaozuo 454000 China College of Computer Science and Software Engineering Shenzhen University Shenzhen 518060 China National High Performance Computing Center at Shenzhen Shenzhen 518055 China

ISBN: (纸本)9781457716362

Data locality has recently been extensively exploited in Cloud computing to improve system performance. However, when schedule Map tasks in Hadoop MapReduce framework working in a heterogeneous environment, existing methods either cannot reduce the occurrence of these Map tasks or injure fairness, thus degrading the system performance. In order to address this problem, this paper proposes a data locality aware scheduling method to improve the Hadoop MapReduce system performance in heterogeneous computing environments. After receiving a request from a requesting node, our method preferentially schedules the task whose input data is stored on the requesting node. If no such tasks exist, our method will select the task whose input data is nearest to the requesting node, and then make a decision on whether to reserve the task for the node storing the input data or schedule the task to the requesting node by transferring the input data to the requesting node on the fly. As a proof of concept, we implement the method in Hadoop-0.20.2. In order to evaluate the performance, we carry out an experimental comparison study on our proposed method against the default scheduling method used in Hadoop-0.20.2. The experiment results show that our proposed method improves the data locality and reduces the normalized execution time as well as the response time of jobs. © 2011 IEEE.

关键词： MapReduce

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Generating Chinese Named Entity Data from a Parallel Corpus 5

Generating Chinese Named Entity Data from a Parallel Corpus

引用

5th International Joint Conference on Natural Language Processing, IJCNLP 2011

作者： Fu, Ruiji Qin, Bing Liu, Ting Research Center for Social Computing and Information Retrieval MOE-Microsoft Key Laboratory of Natural Language Processing and Speech School of Computer Science and Technology Harbin Institute of Technology Harbin China

ISBN: (纸本)9789744665645

Annotating Named Entity Recognition (NER) training corpora is a costly process but necessary for supervised NER systems. This paper presents an approach to generate large-scale Chinese NER training data from an English-Chinese discourse level aligned parallel corpus. Difficulty of NER is different among languages due to their unique features. For example, the performance of English NER systems is usually higher than the Chinese ones on average. In our method, we first employ a high performance NER system on one side of a bilingual corpus. And then, we project the NE labels to the other side according to the word level alignment. At last, we select high-quality labeled sentences using different strategies and generate an NER training corpus. In our experiments, we generate a Chinese NER corpus with 167,100 sentences through an English-Chinese parallel corpus. The system trained on the automatically generated corpus attains a comparable result with the one trained on the manually-annotated corpus. Further experiments show that the NER performance is significantly improved on two different evaluation sets by using the generated training data as an additional corpus to the manually-labeled data. © 2011 AFNLP

关键词： Natural language processing systems

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Towards multi-semantic image annotation with graph regularized exclusive group Lasso 11

Towards multi-semantic image annotation with graph regulariz...

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19th ACM International Conference on Multimedia ACM Multimedia 2011, MM'11

作者： Chen, Xiangyu Yuan, Xiao-Tong Yan, Shuicheng Tang, Jinhui Rui, Yong Chua, Tat-Seng NUS Graduate School for Integrative Sciences and Engineering Singapore Department of Electrical and Computer Engineering Singapore School of Computing NUS Singapore Microsoft Advanced Technology Center China Nanjing University of Science and Technology China

ISBN: (纸本)9781450306164

To bridge the semantic gap between low level feature and human perception, most of the existing algorithms aim mainly at annotating images with concepts coming from only one semantic space, e.g. cognitive or affective. The naive combination of the outputs from these spaces will implicitly force the conditional independence and ignore the correlations among the spaces. In this paper, to exploit the comprehensive semantic of images, we propose a general framework for harmoniously integrating the above multiple semantics, and investigating the problem of learning to annotate images with training images labeled in two or more correlated semantic spaces, such as fascinating nighttime, or exciting cat. This kind of semantic annotation is more oriented to real world search scenario. Our proposed approach outperforms the baseline algorithms by making the following contributions. 1) Unlike previous methods that annotate images within only one semantic space, our proposed multi-semantic annotation associates each image with labels from multiple semantic spaces. 2) We develop a multi-task linear discriminative model to learn a linear mapping from features to labels. The tasks are correlated by imposing the exclusive group lasso regularization for competitive feature selection, and the graph Laplacian regularization to deal with insufficient training sample issue. 3) A Nesterov-type smoothing approximation algorithm is presented for efficient optimization of our model. Extensive experiments on NUS-WIDEEmotive dataset (56k images) with 8×81 emotive cognitive concepts and Object&Scene datasets from NUS-WIDE well validate the effectiveness of the proposed approach. © 2011 ACM.

关键词： Semantics

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The multi-layer spherical helix curve-based 3-D fourier feature

The multi-layer spherical helix curve-based 3-D fourier feat...

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12th International Conference on computer-Aided Design and computer Graphics, CAD/Graphics 2011

作者： Liu, Yujie Li, Zongmin Cao, Weiguo Li, Hua School of Computer Science and Communication Engineering China University of Petroleum Dongying 257062 China National Research Center for Intelligent Computing Systems Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9780769544977

This paper proposes an extended 3-D shape retrieval feature, which is based on a new scheme. In our method, continuous principal component analysis is used to align 3-D models into a canonical position. We then represent 3-D polygonal mesh as a 3-D multi-layer closed curve. It can capture the more feature of the 3-D models. The feature of the 3-D model is extracted from the 3-D closed curve by the Fourier transform. And the experiments show it is more efficient. © 2011 IEEE.

关键词： Principal component analysis

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Image retrieval based on micro-structure descriptor

Image retrieval based on micro-structure descriptor

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作者： Liu, Guang-Hai Li, Zuo-Yong Zhang, Lei Xu, Yong College of Computer Science and Information Technology Guangxi Normal University Guilin 541004 China Department of Computer Science Minjiang University Fuzhou 350108 China Department of Computing Hong Kong Polytechnic University Hong Kong Hong Kong Bio-Computing Research Center Shenzhen Graduate School Harbin Institute of Technology China

This paper presents a simple yet efficient image retrieval approach by proposing a new image feature detector and descriptor, namely the micro-structure descriptor (MSD). The micro-structures are defined based on an edge orientation similarity, and the MSD is built based on the underlying colors in micro-structures with similar edge orientation. With micro-structures serving as a bridge, the MSD extracts features by simulating human early visual processing and it effectively integrates color, texture, shape and color layout information as a whole for image retrieval. The proposed MSD algorithm has high indexing performance and low dimensionality. Specifically, it has only 72 dimensions for full color images, and hence it is very efficient for image retrieval. The proposed method is extensively tested on Corel datasets with 15,000 natural images. The results demonstrate that it is much more efficient and effective than representative feature descriptors, such as Gabor features and multi-textons histogram, for image retrieval. © 2010 Elsevier Ltd. All rights reserved.

关键词： Image retrieval

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The Importance of Precision in Humour Classification

The Importance of Precision in Humour Classification

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12th International Conference on Intelligent Data Engineering and Automated Learning (IDEAL 2011)

作者： Costa, Joana Silva, Catarina Antunes, Mario Ribeiro, Bernardete Computer Science Communication and Research Centre School of Technology and Management Polytechnic Institute of Leiria Portugal Department of Informatics Engineering Center for Informatics and Systems of the University of Coimbra (CISUC) Portugal Center for Research in Advanced Computing Systems (CRACS) Portugal

ISBN: (纸本)9783642238772

Humour classification is one of the most interesting and difficult tasks in text classification. Humour is subjective by nature, yet humans are able to promptly define their preferences. Nowadays people often search for humour as a relaxing proxy to overcome stressful and demanding situations, having little or no time to search contents for such activities. Hence, we propose to aid the definition of personal models that allow the user to access humour with more confidence on the precision of his preferences. In this paper we focus on a Support Vector Machine (SVM) active learning strategy that uses specific most informative examples to improve baseline performance. Experiments were carried out using the widely available Jester jokes dataset, with encouraging results on the proposed framework.

关键词： Support Vector Machine Active Learning Text Classification Humour classification

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Research and implementation on the digital medical image enhancement methods based on gradient smooth and context smooth

Research and implementation on the digital medical image enh...

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2011 7th International Conference on Computational Intelligence and Security, CIS 2011

作者： Liu, Jing Xiong, Jie Computer Network Engineering Technology Center Weinan Normal University Weinan 714000 China Research Institute of Statistical Science and Social Computing Weinan Normal University Weinan 714000 China School of Computer Science and Engineering Xi'an Technological University Xi'an 710032 China

ISBN: (纸本)9780769545844

The digital medical image has its own particularity, in order to diagnose correctly disease, the medical image need be enhanced. According to the features of the digital medical image, the methods based on Gradient smooth and Context smooth are put forward to. The image is smoothed with the smooth function composed by gradient and context in this method. The theory of "Gradient smooth and Context smooth" is used to enhance the image and the enhanced images are operated twice by transformed space stretching. The experiment and the subjective and objective analysis show that the general effect of enhancing the digital medical image by the method in this thesis is superior to histogram equalization, homomorphic filtering and multi-scale Retinex method. © 2011 IEEE.

关键词： Image enhancement

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On alpha-mean of Kullback-Leibler divergences for subspace selection

On alpha-mean of Kullback-Leibler divergences for subspace s...

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2011 8th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2011, Jointly with the 2011 7th International Conference on Natural Computation, ICNC'11

作者： Chen, Si-Bao Wang, Hai-Xian Zhang, Xing-Yi Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei 230039 China Key Lab of Child Development and Learning Science of Ministry of Education Research Center for Learning Science Southeast University Nanjing Jiangsu 210096 China

ISBN: (纸本)9781612841816

Fisher's linear discriminant analysis (FLDA) is one of the most well-known linear subspace selection methods. However, FLDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. Recent results show that maximizing the geometric mean or harmonic mean of Kullback-Leibler (KL) divergences of class pairs can significantly reduce this problem. In this paper, to further reduce the class separation problem, the alpha-mean of divergences as a framework is proposed for subspace selection, with arithmetic mean, geometric mean and harmonic mean as special cases. We named it the maximization of the alpha-mean of all pairs of KL divergences (MAMD) criterion. A quasi-Newton method is applied to solve the optimization problem. Experiments on synthetic data and two datasets in UCI machine learning repository show the validity of MAMD. © 2011 IEEE.

关键词： Newton-Raphson method

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Adaptive discriminant analysis for face recognition from single sample per person

Adaptive discriminant analysis for face recognition from sin...

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IEEE International Conference on Automatic Face and Gesture Recognition

作者： Kan, Meina Shan, Shiguang Su, Yu Chen, Xilin Gao, Wen Digital Media Research Center Institute of Computing Technology CAS Beijing China Key Laboratory of Intelligent Information Processing Chinese Academy of Sciences Beijing China Department of Computer Science University of Caen France Institute for Digital Media Peking University Beijing China School of Computer Science and Technology Harbin Institute of Technology Beijing China

ISBN: (纸本)9781424491407

Discriminant analysis, especially Fisherface and its numerous variants, have achieved great success in face recognition. However, these methods fail to work for face recognition from Single Sample per Person (SSPP), since they need more than one sample per person to estimate the within-class scatter matrix. To break this inability of traditional discriminant analysis, our paper proposes Adaptive Discriminant Analysis (ADA). In our method, the within-class scatter matrix of each enrolled subject is estimated from his/her single sample, by inferring from a generic training set with multiple samples per person. The inference is inspired by a simple intuition that similar person follows similar within-class variations. Specifically, both kNN regression and Lasso regression are explored for this purpose. We evaluate our method on FERET database and a large real-world face database. The results are very impressive compared with dominant traditional solutions to SSPP problem. © 2011 IEEE.

关键词： Discriminant analysis

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Relationship extraction methods based on co-occurrence in web pages and files

Relationship extraction methods based on co-occurrence in we...

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13th International Conference on Information Integration and Web-Based Applications and Services, iiWAS2011

作者： Song, Qiang Watanabe, Yousuke Yokota, Haruo Department of Computer Science Graduate School of Information Science and Engineering Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo Japan Global Scientific Information and Computing Center Tokyo Institute of Technology 2-12-1 Ookayama Meguro-ku Tokyo Japan

ISBN: (纸本)9781450307840

Every day, information on the Web becomes increasingly enriched. Web access is now very useful in many aspects of daily life, particularly for writing documents and programs. In fact, it has become quite usual to edit files while referring to information on the Web. During the file-editing process, we usually visit so many Web pages that we cannot remember all of the relevant ones. Later, if we want to revisit the same Web pages to modify some part of a file, it can be very hard to track down the Web pages originally referred to. In this paper, we propose methods for finding relationships between files and Web pages based on the co-occurrence of data in Web-access logs and file-access logs. These relationships are very useful for revisiting Web pages related to target files. To analyze co-occurrence in these two types of access logs, there are two approaches for merging the logs, involving a trade-off between accuracy and execution time. We call them the Pre-Merge and Post-Merge methods, and we have evaluated these two methods using actual access logs. © 2011 ACM.

关键词： Websites

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