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A Resource Space Model for Dataspace

A Resource Space Model for Dataspace

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Sixth International Conference on Semantics,Knowledge and Grids(第六届语义、知识与网格国际会议 SKG 2010)

作者： Xiaorui Jiang Xiaoping Sun Hai Zhuge Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing Technology CAS Beijing China

Dataspace is a semi-structural data model for the management of large-scale heterogeneous data *** a dataspace,each data object consists of a set of attribute-value pairs to describe the internal properties of the object and their relationships to other objects. The dataspace model provides a flexible query language that supports attribute-value pair-based predicate queries and semantic link queries. In this paper we introduce a Resource Space Model that extends the concepts of dataspace to make it more flexible by incorporating classification semantics. We model a dataspace as a set of Resource Spaces (RS) with each RS representing a kind of resources that share common attributes and can be put into the same category, either according to a user’s knowledge of the world or his query preferences. Our model is suitable for designing a user-tailored semantic view of a dataspace while at the same time without losing the schema-later data-centric nature. A practical query language is introduced to implement flexible query operations on the resource spaces of the dataspace. Examples show how the proposed model and language support both the schema query and the data query.

关键词： Semantics Data models Argon Portals Organizations Database languages Resource description framework

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On dynamic weighting of data in clustering with K-alpha means

On dynamic weighting of data in clustering with K-alpha mean...

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2010 20th International Conference on Pattern Recognition, ICPR 2010

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

ISBN: (纸本)9780769541099

Although many methods of refining initialization have appeared, the sensitivity of K-Means to initial centers is still an obstacle in applications. In this paper, we investigate a new class of clustering algorithm, K-Alpha Means (KAM), which is insensitive to the initial centers. With K-Harmonic Means as a special case, KAM dynamically weights data points during iteratively updating centers, which deemphasizes data points that are close to centers while emphasizes data points that are not close to any centers. Through replacing minimum operator in K-Means by alpha-mean operator, KAM significantly improves the clustering performances. © 2010 IEEE.

关键词： Clustering algorithms

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Subspace selection using semi-supervised harmonic mean of Kullback-Leibler divergences

Subspace selection using semi-supervised harmonic mean of Ku...

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2010 7th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2010

作者： Chen, Si-Bao Wang, Hai-Xian Luo, Bin Key Lab of Intelligent Computing and Signal Processing of Ministry of Education School of Computer Science and Technology Anhui University Hefei Anhui 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)9781424459346

In many areas of pattern recognition and machine learning, subspace selection is an essential step. Fisher's linear discriminant analysis (LDA) is one of the most well-known linear subspace selection methods. However, LDA suffers from the class separation problem. The projection to a subspace tends to merge close class pairs. A recent result, named maximizing the geometric mean of Kullback-Leibler (KL) divergences of class pairs (MGMD), can significantly reduce the class separation problem. Furthermore, maximizing the harmonic mean of Kullback-Leibler (KL) divergences of class pairs (MHMD) emphasizes smaller divergences more than MGMD, and deals with the class separation problem more effectively. However, in many applications, labeled data are very limited while unlabeled data can be easily obtained. The estimation of divergences of class pairs is unstable using inadequate labeled data. To take advantage of unlabeled data for subspace selection, semi-supervised MHMD (SSMHMD) is proposed using graph Laplacian as normalization. Quasi-Newton method is adopted to solve the optimization problem. Experiments on synthetic data and real image data show the validity of SSMHMD. ©2010 IEEE.

关键词： Discriminant analysis

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Salient object extraction for user-targeted video content association

Salient object extraction for user-targeted video content as...

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作者： Li, Jia Yu, Han-Nan Tian, Yong-Hong Huang, Tie-Jun Gao, Wen Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China School of EE and CS Peking University Beijing 100871 China

The increasing amount of videos on the Internet and digital libraries highlights the necessity and importance of interactive video services such as automatically associating additional materials (e.g., advertising logos and relevant selling information) with the video content so as to enrich the viewing experience. Toward this end, this paper presents a novel approach for user-targeted video content association (VCA). In this approach, the salient objects are extracted automatically from the video stream using complementary saliency maps. According to these salient objects, the VCA system can push the related logo images to the users. Since the salient objects often correspond to important video content, the associated images can be considered as content-related. Our VCA system also allows users to associate images to the preferred video content through simple interactions by the mouse and an infrared pen. Moreover, by learning the preference of each user through collecting feedbacks on the pulled or pushed images, the VCA system can provide user-targeted services. Experimental results show that our approach can effectively and efficiently extract the salient objects. Moreover, subjective evaluations show that our system can provide content-related and user-targeted VCA services in a less intrusive way. © 2010 Zhejiang University and Springer-Verlag Berlin Heidelberg.

关键词： Digital libraries

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The Interactive computing Model for Cyber Physical Society

The Interactive Computing Model for Cyber Physical Society

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Sixth International Conference on Semantics,Knowledge and Grids(第六届语义、知识与网格国际会议 SKG 2010)

作者： Xiaoping Sun Hai Zhuge Xiaorui Jiang Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China

With the permeation of information technology intothe physical world and human society, we are on the way to a Cyber Physical Society (CPSocio). A CPSocio inter-connects the nature, the cyber space, and the society, so as to provide human beings with a better living and working environment. researches on CPSocio will lead to a new revolution of information science and technology. In realizing CPSocio, semantics is the most fundamental problem. It is the foundation of all the intelligent activities such as communication, interaction, and cooperation in CPSocio. We are facing various scientific challenges to understand and clarify principles and models of the computing in CPSocio. In this paper we focus on the interactive computing model of Cyber Physical Society, discussing a possible architecture and computing model that enable future intelligent distributed services in CPSocio. The proposed model focuses on the interactive computation emerged from self-interpretation, self-organization and interactions of individual objects. Selfinterpretation enables objects to actively express their own semantic information to others. Interaction among objects will help achieving computing solutions in open, dynamic, limited and heterogeneous environments with partial available information and services. The model aims at providing a feasible framework for systematically tackling key problems and building intelligent services in CPSocio.

关键词： Semantics Computational modeling Data models Artificial intelligence Humans Object recognition Servers

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C*-tree: A Multi-Dimensional Index Structure for Resource Space Model

C*-tree: A Multi-Dimensional Index Structure for Resource Sp...

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Sixth International Conference on Semantics,Knowledge and Grids(第六届语义、知识与网格国际会议 SKG 2010)

作者： Qiang Zeng Hai Zhuge Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

Resource Space Model (RSM) is a semantic data model for specifying, organizing, and retrieving resources based on classification of *** efficient index mechanism is critical for its implementation. However, traditional index mechanisms are not well suitable to resource spaces because the spaces are discrete and hierarchical. This paper proposes a new multidimensional index structure C*-tree. It employs boxes to represent resources so that the containment of boxes can reflect the hierarchical structure of resources. The metric function defined in the C*-tree is able to gather close resources in the index structure. To avoid overlap between bounding boxes, a new restricted bounding box is further introduced. Moreover, the insertion algorithms based on the data partition approach can fully utilize characteristics of RSM. The C*-tree is scalable and efficient on both the number of dimension and the amount of data for different distributions.

关键词： Indexes Semantics Encoding Measurement Data models Approximation methods Partitioning algorithms

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Cyber Physical Society

Cyber Physical Society

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Sixth International Conference on Semantics,Knowledge and Grids(第六届语义、知识与网格国际会议 SKG 2010)

作者： Hai Zhuge Knowledge Grid Research Group Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China

Natural physical space provides material basis for the birth and evolution of human beings and *** progress of human society has created the cyber space. With the rapid development of information technology, the cyber space is connecting physical space, social space and mental space to form a new world - Cyber Physical Society. The way to explore the cyber physical society is different from the way to explore the natural physical space and society. This paper describes the ideal of the Cyber Physical Society, and presents its distinguished characteristics and scientific issues. research on the Cyber Physical Society could lead to the revolution of society, science and technology.

关键词： Semantics Space technology Aerospace electronics Humans Materials Communities Sensors

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Efficient incremental decoding for tree-to-string translation

Efficient incremental decoding for tree-to-string translatio...

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Conference on Empirical Methods in Natural Language processing, EMNLP 2010

作者： Huang, Liang Mi, Haitao Information Sciences Institute University of Southern California 4676 Admiralty Way Marina del Rey CA 90292 United States Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences P.O. Box 2704 Beijing 100190 China

ISBN: (纸本)1932432868

Syntax-based translation models should in principle be efficient with polynomially-sized search space, but in practice they are often embarassingly slow, partly due to the cost of language model integration. In this paper we borrow from phrase-based decoding the idea to generate a translation incrementally left-to-right, and show that for tree-to-string models, with a clever encoding of derivation history, this method runs in average-case polynomial-time in theory, and linear-time with beam search in practice (whereas phrase-based decoding is exponential-time in theory and quadratic-time in practice). Experiments show that, with comparable translation quality, our tree-to-string system (in Python) can run more than 30 times faster than the phrase-based system Moses (in C++). © 2010 Association for Computational Linguistics.

关键词： Decoding

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Application of AWE to scattering analysis of the double-negative medium

Application of AWE to scattering analysis of the double-nega...

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2010 9th International Symposium on Antennas Propagation and EM Theory, ISAPE 2010

作者： Sun, Yu-Xin Chen, Ming-Sheng Wu, Xian-Liang Yang, Mei Wang, Hui Key Lab. of Intelligent Computing and Signal Processing Anhui University Ministry of Education Hefei China Department of Physics and Electronic Engineering Hefei Normal University Hefei China School of Information Science and Technology University of Science and Technology of China Hefei 230026 China

ISBN: (纸本)9781424469062

The PMCHWT equation of the double negative media (DNG) is obtained based on its constitutive relationship. And the surface currents and radar cross section (RCS) at a single frequency point is computed by Method of moments (MOM). The asymptotic waveform evaluation (AWE) technique for dispersive dielectric medium is deduced and apllied to electromagnetic scattering analysis of double-negative medium within a given frequency band. ©2010 IEEE.

关键词： Method of moments

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Automatic video genre categorization and event detection techniques on large-scale sports data 10

Automatic video genre categorization and event detection tec...

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Proceedings of the 2010 Conference of the Center for advanced Studies on Collaborative research

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

This paper presents an efficient and robust automatic process for large-scale sports video analysis. The proposed system firstly identifies the genre of the query video, and then accomplishes the interesting event detection task. The significance of this framework is its automatic characteristic in testing with minimum human involvement in training, as well as the scalability and expansibility in dealing with a large-scale dataset. Domain-knowledge independent local features are extracted from an input video sequence and a histogram based distribution representation is created using the bag-of-visual-words (BoW) model. In genre categorization, k-nearest neighbor (k-NN) classifiers with various dissimilarity measures are assessed and evaluated analytically. For the event detection, a hidden conditional random field (HCRF) structured prediction model is utilized. Overall, this framework demonstrates the efficiency and accuracy in processing voluminous data from sports collection and achieves various tasks in video analysis. It also demonstrates a potential technology transformation from the "laboratory bench" to commercial applications. © 2010 Ning Zhang, Ling-Yu Duan, Qing-ming Huang, Lingfang Li, Wen Gao and Ling Guan.

关键词： Sports

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