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IEEE International Conference on Big Data

作者： Bo Zhang Zhong-Zhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Many classification techniques work well only under a common assumption that the training and test data are drawn from the same feature space and the same distribution. However, big velocity data usually show disobedience of this assumption. For example, in the field of web-document classification, new document is continuously emerging every day. Transfer learning aims at leveraging the knowledge in labeled source domains to predict the unlabeled data in a target domain, where the distributions are different in domains. As one of the important research directions of transfer learning, one kind of approaches focus on the correspondence between pivot features and all the other specific features from different domains, to extract some relevant features that may reduce the difference between the domains, have attracted wide attention and study. However, the limitation caused by the vague meanings in different domains prevents these algorithms from further improvement. To tackle this problem, we propose a cross-domain canonical correlation analysis algorithm called CD-CCA by applying Canonical Correlation Analysis (CCA) to transfer learning. CD-CCA can learn a semantic space of multi-view correspondences from different domains respectively and transfer the knowledge by dimensionality reduction in a multi-view way. Experimental results on the 144×6 classification problems in 20Newsgroups, show that CD-CCA can significantly improve the prediction accuracy.

关键词： Correlation Algorithm design and analysis Classification algorithms Feature extraction Semantics Vectors Mutual information

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Distributed query processing in an ad-hoc semantic web data sharing system

Distributed query processing in an ad-hoc semantic web data ...

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2013 IEEE 37th Annual Computer Software and Applications Conference, COMPSAC 2013

作者： Zhou, Jing Bochmann, Gregor V. Shi, Zhongzhi School of Computer Science Communication University of China Beijing China School of Electrical Engineering and Computer Science University of Ottawa ON Canada Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769549798

Sharing the Semantic Web data in proprietary datasets in which data is encoded in RDF triples in a decentralized environment calls for efficient support from distributed computing technologies. The highly dynamic ad-hoc settings that would be pervasive for Semantic Web data sharing among personal users in the future, however, pose even more demanding challenges for the enabling technologies. We extend previous work on a hybrid P2P architecture for an ad-hoc Semantic Web data sharing system which better models the data sharing scenario by allowing data to be maintained by its own providers and exhibits satisfactory scalability owing to the adoption of a two-level distributed index and hashing techniques. Additionally, we propose efficient distributed processing of SPARQL queries in such a context and explore optimization techniques that build upon distributed query processing for database systems and relational algebra optimization. We anticipate that our work will become an indispensable, complementary approach to making the Semantic Web a reality by delivering efficient data sharing and reusing in an ad-hoc environment. © 2013 IEEE.

关键词： Query processing

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Adaptive Particle Filter with Estimation Windows

Adaptive Particle Filter with Estimation Windows

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2013年中国智能自动化学术会议

作者： Peng Li Jian Tang College of Information and Technology Key Laboratory of Intelligent Computing and Information ProcessingMinistry of EducationXiangtan University

Particle filter is well suited to estimate the state of non-linear non-Gaussian dynamic systems,which comes at the cost of higher computational *** in many real time applications,it must deal with constraints imposed by limited computational *** deal with this question,we distribute the samples among the different observations arriving during a filter update, the novel algorithm represents densities over the state space by mixtures of sample *** contribution of this paper is to increasing the efficiency of particle filters by adapting the size of sample sets during the estimation *** to the relative entropy theory and particle number controller idea,we choose the number of samples,decrease computation overhead.A simulation of the classic HARD bearing only tracking problem is presented,the results show that the novel algorithm performs better than generic particle filter.

关键词： Particle filter Estimation window Relative entropy Particle number controller

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Architecture-Based Integrated Management of Cloud Resources

Architecture-Based Integrated Management of Cloud Resources

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International Conference on Cloud computing and Big Data (CloudCom-Asia)

作者： Xing Chen Ying Zhang Xiaodong Zhang Xianghan Zheng Wenzhong Guo Guolong Chen Fujian Provincial Key Laboratory of Networking Computing and Intelligent Information Processing Key Laboratory of High Confidence Software Technologies (Ministry of Education)

Cloud management faces with great challenges, due to the diversity of Cloud resources and ever-changing management requirements. For constructing a management system to satisfy a specific management requirement, a redevelopment solution based on existing management system is usually more practicable than developing the system from scratch. However, the difficulty and workload of redevelopment are also very high. As the architecture-based runtime model is causally connected with the corresponding running system automatically, constructing an integrated Cloud management system based on the architecture-based runtime models of Cloud resources can benefit from the model-specific natures, and thus reduce the development workload. Therefore, in this paper, we present an architecture-based approach to managing diverse Cloud resources. First of all, the manageability (such as APIs, configuration files and scripts) of Cloud resources are abstracted as runtime models, which can automatically and immediately propagate any observable runtime changes of the target resources to the corresponding architecture models, and vice versa. Then, a customized model is constructed according to the specific Cloud management requirement. Finally, the operations on the customized model are mapped to the ones on Cloud resource runtime models through model transformation. Thus, all the management tasks can be carried out through executing operations on the customized model. The experiment on a real-world cloud demonstrates the feasibility, effectiveness and benefits of the new approach to integrated management of Cloud resources.

关键词： Runtime Servers Virtual machining Software Computer architecture Complexity theory Synchronization

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Research of maneuvering target tracking based on particle filter

Research of maneuvering target tracking based on particle fi...

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Chinese Automation Congress (CAC)

作者： Xia Li Peng Li Yougui Guo Zhengbin Shen Ministry of Education Key Laboratory of Intelligent Computing & Information Processing Xiangtan city Hunan province China

The essence of maneuvering target tracking is mainly including maneuvering target modeling, maneuvering target detection or maneuvering target identification and filtering algorithm. In this paper, the maneuvering target model was described by the cooperative turn model, and tracked by the particle filter algorithm. The resample technique is introduced to overcome the problem of particle degradation in standard particle filter. Finally, we finished simulation experiments by Matlab, and compared the particle filter algorithm with the extended kalman filter algorithm, the results show that particle filter with the resample technique has a better performance in tracking precision, computational complexity, real-time performance and stability, it is a more effective method for maneuvering target tracking.

关键词： Target tracking Particle filters Mathematical model Filtering algorithms Noise Probability density function Computational modeling

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Discussion on Integrated Specialty Reform of Communication Engineering

Discussion on Integrated Specialty Reform of Communication E...

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2nd International Conference on Science and Social Research(ICSSR 2013)

作者： Jun Zhu Xiao-Hui Li Yu-Fa Sun Key Laboratory of Intelligent Computing & Singnal Processing Ministry of Education School of Electronic Information Engineering Anhui University

ISBN: (纸本)9781629939742

Communication engineering specialty is an engineering practical and very strong applied specialty. Practice teaching plays an important role of cultivating students' scientific thinking methods, scientific research ability and innovation ability. Through integrated specialty reform, we improve the practice teaching conditions further, optimize the practice teaching content, innovate the teaching mode, strengthen the teaching team and promote the combination of the cultivation of talents, production-practice and social practice, thus improving students' innovation consciousness and practice ability.

关键词： communication engineering specialty, talents training mode, integrated specialty reform, practice teaching link.

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Discriminative learning with natural annotations: Word segmentation as a case study

Discriminative learning with natural annotations: Word segme...

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51st Annual Meeting of the Association for Computational Linguistics, ACL 2013

作者： Jiang, Wenbin Sun, Meng Lü, Yajuan Yang, Yating Liu, Qun Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Multilingual Information Technology Research Center Xinjiang Technical Institute of Physics and Chemistry Chinese Academy of Sciences China Centre for Next Generation Localisation Faculty of Engineering and Computing Dublin City University Ireland

ISBN: (纸本)9781937284503

Structural information in web text provides natural annotations for NLP problems such as word segmentation and parsing. In this paper we propose a discriminative learning algorithm to take advantage of the linguistic knowledge in large amounts of natural annotations on the Internet. It utilizes the Internet as an external corpus with massive (although slight and sparse) natural annotations, and enables a classifier to evolve on the large-scaled and real-time updated web text. With Chinese word segmentation as a case study, experiments show that the segmenter enhanced with the Chinese wikipedia achieves significant improvement on a series of testing sets from different domains, even with a single classifier and local features. © 2013 Association for Computational Linguistics.

关键词： Learning algorithms

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ROBUST MULTI-PATCH TRACKING

ROBUST MULTI-PATCH TRACKING

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IEEE International Conference on Image processing

作者： Shanxin Yuan Jun Miao Laiyun Qing Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781479923427

In this paper, we propose a robust and fast multi-patch visual tracking algorithm within the Bayesian inference framework. The target template is initialized by selecting the object in the first frame manually and dividing it into small patches. For one certain frame, target candidates are sampled with the state transition model. Each candidate is divided into patches in the same way as the target template. By comparing the candidate's patches with the corresponding template patches, we can get the candidate's likelihood. The tracking result is the candidate which Maximum a Posteriori estimation. After that, tracking is continued using the Bayesian state inference and template update. Our approach can handle appearance variation, occlusion, illumination change, scale variation, rotation and cluttered background. The tracker is fast and performs favorably against several state-of-the-art trackers on challenging sequences.

关键词： Visual tracking Bayesian inference multi-patch fast robust Bayesian inference visual tracking Fasting jigs(templates) tracking Maximum a posteriori estimation Robustness Patches State Change candidate species

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EMPLOYING PLSA MODEL AND MAX-BISECTION FOR REFINING IMAGE ANNOTATION

EMPLOYING PLSA MODEL AND MAX-BISECTION FOR REFINING IMAGE AN...

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IEEE International Conference on Image processing

作者： Dongping Tian Wenbo Zhang Xiaofei Zhao Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9781479923427

We present a new method for refining image annotation by fusing probabilistic latent semantic analysis (PLSA) with max-bisection (MB). We first construct a PLSA model with asymmetric modalities to estimate the posterior probabilities of each annotating keyword for an image, and then a label similarity graph is built by a weighted linear combination of label similarity and visual similarity. Followed by the rank-two relaxation heuristics over the constructed label graph is employed to further mine the correlation of the keywords so as to capture the refining annotation, which plays a critical role in semantic based image retrieval. The novelty of our method mainly lies in two aspects: exploiting PLSA to accomplish the initial semantic annotation task and implementing max-bisection based on the rank-two relaxation algorithm over the weighted label graph to refine the candidate annotations generated by the PLSA. We evaluate our method on the standard Corel dataset and the experimental results are competitive to several state-of-the-art approaches.

关键词： Refining image annotation PLSA EM max-bisection image retrieval image retrieval images ANNOTATIONS Refining labelled graph Line graph Linear Combination Purification keyWORD

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The Sound and Complete <i>R</i>-Calculi with Respect to Pseudo-Revision and Pre-Revision

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International Journal of Intelligence Science 2013年第2期3卷 110-117页

作者： Wei Li Yuefei Sui Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China State Key Laboratory of Software Development Environment Beijing University of Aeronautics and Astronautics Beijing China

The AGM postulates ([1]) are for the belief revision (revision by a single belief), and the DP postulates ([2]) are for the iterated revision (revision by a finite sequence of beliefs). Li [3] gave an R-calculus for R-configurations △|Γ, where Δ is a set of literals, and Γ is a finite set of formulas. We shall give two R-calculi such that for any consistent set Γ and finite consistent set △ of formulas in the propositional logic, in one calculus, there is a pseudo-revision Θ of Γ by Δ such that is provable and and in another calculus, there is a pre-revision Ξ of Γ by Δ such that is provable, and for some pseudo-revision Θ;and prove that the deduction systems for both the R-calculi are sound and complete with the pseudo-revision and the pre-revision, respectively.

关键词： Belief Revision R-Calculus Maximal Consistent Set Pseudo-Revision Pre-Revision

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