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Bilingually-constrained (monolingual) shift-reduce parsing

Bilingually-constrained (monolingual) shift-reduce parsing

2009 Conference on Empirical Methods in Natural Language processing, EMNLP 2009, Held in Conjunction with ACL-IJCNLP 2009

作者： Huang, Liang Jiang, Wenbin Liu, Qun Google Research 1350 Charleston Rd. Mountain View CA 94043 United States Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

Jointly parsing two languages has been shown to improve accuracies on either or both sides. However, its search space is much bigger than the monolingual case, forcing existing approaches to employ complicated modeling and crude approximations. Here we propose a much simpler alternative, bilingually-constrained monolingual parsing, where a source-language parser learns to exploit reorderings as additional observation, but not bothering to build the target-side tree as well. We show specifically how to enhance a shift-reduce dependency parser with alignment features to resolve shift-reduce conflicts. Experiments on the bilingual portion of Chinese Treebank show that, with just 3 bilingual features, we can improve parsing accuracies by 0.6% (absolute) for both English and Chinese over a state-of-the-art baseline, with negligible (∼6%) efficiency overhead, thus much faster than biparsing. © 2009 ACL and AFNLP.

关键词： Forestry

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Organizing structured deep web sources with semantic inference

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Journal of Computational information Systems 2009年第3期5卷 1157-1165页

作者： Huang, Li Fang, Wei Chen, Hongpin Zhao, Pengpeng Cui, Zhiming Jiangsu Key Laboratory of Computer Information Processing Technology Soochow University Suzhou 215006 China Institute of Intelligent Information Processing and Application Soochow University Jiangsu Suzhou 215006 China

Deep Web sources classification is one of key steps in Large-scale data integration, and structured query interface of Deep Web serves as a valid approach for research on online databases organization by domains. This paper proposes a novel classification strategy on Deep Web sources. Decisive features and co-occurrence features could be obtained by semantic inference from visible features of query interface, which enrich semantic features in form. Integration of semantic inference and machine learning method effectively can further improve traditional classification performance on Deep Web sources. Experimental results on real web datasets show that our method is improved with higher classification accuracy. 1553-9105/ Copyright © 2009 Binary information Press.

关键词： Data integration

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Identifying query interfaces of deep web entries automatically

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Journal of Computational information Systems 2009年第3期5卷 1477-1485页

作者： Cui, Zhiming Fang, Wei Huang, Li Xian, Xuefeng Zhang, Shukui Jiangsu Provincial Key Laboratory of Computer Information Processing Technology Soochow University Suzhou 215006 China Institute of Intelligent Information Processing and Application Soochow University Suzhou 215006 China

A large number of high-quality web information is deeply hidden in the Web, which can not be indexed by conventional search engines, be called Deep Web. Because query interface is the only entrance to the Deep Web, we should find Deep Web query entries firstly. In this paper, we propose a new strategy that automatically and accurately identifies Deep Web entries based on Maximum Entropy and Bayes classifier from features that extracted from web form, link and page. Our experiments over real web pages show that the new approach can classify Deep Web entries accurately and efficiently. 1553-9105/ Copyright © 2009 Binary information Press.

关键词： Search engines

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A Dynamic Description Logic-Based Formalism for RBAC

A Dynamic Description Logic-Based Formalism for RBAC

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International Conference on Computer Sciences and Convergence information technology (ICCIT)

作者： Li Ma Shilong Ma Jianghua Lv Yuefei Sui Department of Computer Science Beihang University Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

ISBN: (纸本)9781424452446

Applications in the open and dynamic environment become more intelligent and complicated. To secure these applications is a big challenge. RBAC model, as a de facto standard in access control field, is widely used in many applications. But the lack of dynamic and formal method to describe RBAC makes the model can't completely adapt to the open and dynamic environment. To solve this problem, we introduce a three level RBAC model which unifies the administrative components, the administrative actions and the regular RBAC components, and also proposes a dynamic description logic, called DDL RBAC , to formalize the three level model. Based on the formal description of RBAC with DDL RBAC , an executable action decision algorithm to guarantee the dynamic consistency of systems is also presented.

关键词： Logic Access control Authorization Data security information security Mathematical model Permission information technology Computer science Laboratories

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Reconstruction of images from compressive sensing based on the stagewise fast LASSO

Reconstruction of images from compressive sensing based on t...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral Image processing and Pattern Recognition

作者： Wu, Jiao Liu, Fang Jiao, Licheng School of Computer Science and Technology Xidian University Xi'an 710071 China Key Laboratory of Intelligent Perception and Image Understanding of Ministry of Education of China Xi'an 710071 China Institute of Intelligent Information Processing Xidian University Xi'an 710071 China College of Sciences China Jiliang University Hangzhou 310018 China

ISBN: (纸本)9780819478092

Compressive sensing (CS) is a theory about that one may achieve a nearly exact signal reconstruction from the fewer samples, if the signal is sparse or compressible under some basis. The reconstruction of signal can be obtained by solving a convex program, which is equivalent to a LASSO problem with l1-formulation. In this paper, we propose a stage-wise fast LASSO (StF-LASSO) algorithm for the image reconstruction from CS. It uses an insensitive Huber loss function to the objective function of LASSO, and iteratively builds the decision function and updates the parameters by introducing a stagewise fast learning strategy. Simulation studies in the CS reconstruction of the natural images and SAR images widely applied in practice demonstrate that the good reconstruction performance both in evaluation indexes and visual effect can be achieved by StF-LASSO with the fast recovered speed among the algorithms which have been implemented in our simulations in most of the cases. Theoretical analysis and experiments show that StF-LASSO is a CS reconstruction algorithm with the low complexity and stability. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Compressed sensing

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Automatic sports genre categorization and view-type classification over large-scale dataset 09

Automatic sports genre categorization and view-type classifi...

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17th ACM International Conference on Multimedia, MM'09, with Co-located Workshops and Symposiums

作者： Li, Lingfang Zhang, Ning Duan, Ling-Yu Huang, Qingming Du, Jun Guan, Ling Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Ryerson Multimedia Research Laboratory Ryerson University Toronto ON Canada Institute of Digital Media Peking University Beijing 100871 China Graduate University of Chinese Academy of Sciences Beijing 100190 China NEC Research Labs. China Beijing 100084 China

ISBN: (纸本)9781605586083

This paper presents a framework with two automatic tasks targeting large-scale and low quality sports video archives collected from online video streams. The framework is based on the bag of visual-words model using speeded-up robust features (SURF). The first task is sports genre categorization based on hierarchical structure. Following on the second task which is based on automatically obtained genre, views are classified using support vector machines (SVMs). As a consequence, the views classification result can be used in video parsing and highlight extraction. As compared with state-of-the-art methods, our approach is fully automatic as well as domain knowledge free and thus provides a better extensibility. Furthermore, our dataset consists of 14 sport genres with 6850 minutes in total. Both sport genre categorization and view type classification have more than 80% accuracy rates, which validate this framework's robustness and potential in web-based applications. Copyright 2009 ACM.

关键词： Support vector machines

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A novel two-tier Bayesian based method for hair segmentation

A novel two-tier Bayesian based method for hair segmentation

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IEEE International Conference on Image processing

作者： Dan Wang Shiguang Shan Wei Zeng Hongming Zhang Xilin Chen Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China NEC Laboratories Beijing China

In this paper, a novel two-tier Bayesian based method is proposed for hair segmentation. In the first tier, we construct a Bayesian model by integrating hair occurrence prior probabilities (HOPP) with a generic hair color model (GHCM) to obtain some reliable hair seed pixels. These initial seeds are further propagated to their neighborhood pixels by utilizing segmentation results of mean shift, to obtain more seeds. In the second tier, all of these selected seeds are used to train a hair-specific Gaussian model, which are combined with HOPP to build the second Bayesian model for pixel classification. Mean shift results are further utilized to remove holes and spread hair regions. The experimental results illustrate the effectiveness of our approach.

关键词： Bayesian methods Hair Image segmentation Content addressable storage Face detection information processing Computers National electric code Diversity reception Pixel

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Image Reconstruction by Sparse Coding and Selective Attention

Image Reconstruction by Sparse Coding and Selective Attentio...

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Congress on Image and Signal processing, CISP

作者： Zhiqing Li Zhiping Shi Zhixin Li Zhongzhi Shi College of Information Engineering Xiangtan University Xiangtan China Chinese Academy and Sciences Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Sparse coding theory demonstrates that the neurons in primary visual cortex form a sparse representation of natural scenes in the viewpoint of statistics. In this paper, inspired by the research of selective attention in psychology, we propose a novel self-adaptive algorithm to further reduce the activated variables. The experimental results show that the quality of reconstructed images obtained by our method is satisfying. Moreover, combining selective attention and sparse coding our method evidently decreases the number of coefficients which may be activated and preserves the main information at the same time.

关键词： Image reconstruction Image coding Neurons information processing Layout Vectors Laboratories Computers Codes Statistics

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Path planning using FMM with direction and curvature constrained

Path planning using FMM with direction and curvature constra...

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MIPPR 2009 - Remote Sensing and GIS Data processing and Other Applications: 6th International Symposium on Multispectral Image processing and Pattern Recognition

作者： Li, Shidong Ding, Mingyue Cai, Chao Institute for Pattern Recognition and Artificial Intelligence National Lab. for Multi-spectral Information Processing Technologies Huazhong University of Science and Technology Wuhan 430074 China Hubei University for Nationalities Enshi Hubei 445000 China College of Life Science and Technology Image Processing and Intelligent Control Key Laboratory of Education Ministry of China Huazhong University of Science and Technology Wuhan 430074 China

ISBN: (纸本)9780819478092

It is difficult to meet both direction and curvature constraints for traditional Fast Marching (FM) method in path planning. Based on adjusting the cost function in Eiknoal equation-the control equation for FM, a new model for computing the integrated cost function was presented in this paper. A relationship formula about curvature radius was obtained and three kinds of adjusting strategies were given;two of them were used to modify the route to meet with the requires of turning constraint in this paper. Experiments showed that the improved model can be used to plan the path with FMM for agent such as unmanned aerial vehicle (UAV) or robot, which is limited to pass through the scene matching areas. And our preliminary experiments demonstrated that the strategies are feasible and efficient to obtain path with certain curvature radius. The model can also be used to represent the problem such as an aircraft flying in a flow field. © 2009 Copyright SPIE - The International Society for Optical Engineering.

关键词： Motion planning

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A generic approach to classify sports video shots and its application in event detection 09

A generic approach to classify sports video shots and its ap...

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1st International Conference on Internet Multimedia computing and Service, ICIMCS 2009

作者： Li, Lingfang Duan, Ling-Yu Huang, Qingming Du, Jun Gao, Wen Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Institute of Digital Media Peking University Beijing 100871 China Graduate University of Chinese Academy of Sciences Beijing 100190 China NEC Research Labs. China Beijing 100084 China

ISBN: (纸本)9781605588407

Shot type is useful information for semantic sports video analysis. Most existing approaches utilize predefined rules and domain knowledge to derive shot types in sports video. Although these methods have achieved promising results in some specific games, it is hard to extend them from one sport to another. To address this problem, we propose a generic approach to classify shots in sports video. Our approach utilizes bag of visual words model to represent key frame for each shot based on Scale Invariant Feature Transform (SIFT) feature points;either Support Vector Machine (SVM) or Probabilistic Latent Semantic Analysis (PLSA) are then employed to classify key frame to determine shot type. As our approach relies little on domain knowledge, it can be more easily extended to different sports. We have evaluated our shot classification approach over five types of sports video and have achieved promising results. To show the usefulness and effectiveness of our shot classification, we apply the results of shot type to detect events in basketball video via a generative-discriminative model. In addition, we have observed that some common visual parts frequently appear across various shots in the same sport or even different but relevant sports. For instance, soccer and basketball are relevant sports in the sense of field-ball game. Motivated by this observation, we attempt to alleviate the problem of insufficient sports video data in some applications by sharing these visual parts across different but relevant kinds of sports. Copyright 2009 ACM.

关键词： Sports

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