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2012 13th IEEE International Conference on Multimedia and Expo, ICME 2012

作者： Zhang, Xinfeng Xiong, Ruiqin Ma, Siwei 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 Institute of Digital Media Peking University Beijing 100871 China

ISBN: (纸本)9781467316590

Block transform coding using discrete cosine transform is the most popular approach for image compression. However, many annoying blocking artifacts are generated due to coarse quantization on transform coefficients independently. This paper proposes an effective blocking artifacts reduction method by estimating the transform coefficients from their quantized version. In the proposed scheme, we estimate the transform coefficients based on an image statistic model and non-local similarity among blocks in transform domain. The parameters used in our proposed scheme are discussed and adaptively selected. Extensive experimental results show that our proposed method significantly reduces blocking artifacts and improves the subjective and the objective quality of block transform coded images. © 2012 IEEE.

关键词： Discrete cosine transforms

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Evaluating Structure of Complex Networks by Navigation Entropy

Evaluating Structure of Complex Networks by Navigation Entro...

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第8届语义知识与网络国际会议(2012 Eighth International Conference on Semanties,Knowledge and Grids )(SKG2012)

作者： Xiaoping Sun Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Complex networks are extensively studied in various areas such as social networks,biological networks,Internet and networks have many characters such as small-diameter,higher cluster and power-law degree ***-world is evolved for efficient information transformation and ***,navigation is an important functional character of *** researches mostly focus on understanding the navigability of small-world networks by analyzing the diameter and the routing *** this paper,we use the navigability to model the basic structural complexity of a *** is,given a network topology,we need a model to evaluate how complex the topology *** network complexity models have been proposed but none of them consider the navigability factor of the network *** believe that using the navigability factor to evaluate the network structural complexity is a feasible and reasonable *** use the adjacent matrix to build a navigation transition matrix and evaluate the randomness of random walks on the transition matrix by defining navigation entropy on *** use the iteration of the random walk matrix to evaluate the navigability of a network and the complexity of *** is,the higher the navigation entropy,the higher the randomness of a *** lower the navigation entropy,the higher the structure of a *** apply the navigation entropy model on a set of structural and random network topologies to show how the model can show the different complexity of networks.

关键词： navigation entropy structure complexity complex network

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Memory performance prediction of web server applications based on grey system theory

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14th Asia Pacific Web technology Conference, APWeb 2012

作者： Huang, Faliang Zhang, Shichao Yuan, Changan Zhong, Zhi Faculty of Software Fujian Normal University Fuzhou 350007 China Faculty of Engineering and Information Technology University of Technology Broadway P.O. Box 123 Sydney NSW 2007 Australia Science Computing and Intelligent Information Processing GuangXi Higher Education Key Laboratory Nanning 530023 China

ISBN: (纸本)9783642292521

With the success of internet, recently more and more companies start to run web-based business. While running e-business sites, many companies have encountered unexpected degeneration of their web server applications performance, which may lead to loss of customers. Many managers wish to have a decision-support tool that cancan answer such questions, such as "will my web server applications performance degenerate?", and "what are the main reasons of the degenerations?". In this paper we first propose a new memory performance prediction model of web server applications based on grey system theory. And then, a software system "Memory Performance Manager" (MPM) is developed for predicting memory performance of the web server applications. Massive experiments demonstrate that the effectiveness of MPM's in predicting web server memory performances. © 2012 Springer-Verlag Berlin Heidelberg.

关键词： Managers

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Parallel implementation of apriori algorithm based on MapReduce

Parallel implementation of apriori algorithm based on MapRed...

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13th ACIS International Conference on Software Engineering, Artificial Intelligence, Networking, and Parallel/Distributed computing, SNPD 2012

作者： Li, Ning Zeng, Li He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100139 China Key Lab. of Machine Learning and Computational Intelligence College of Mathematics and Computer Science Hebei University Baoding 071002 Hebei China

ISBN: (纸本)9780769547619

Searching frequent patterns in transactional databases is considered as one of the most important data mining problems and Apriori is one of the typical algorithms for this task. Developing fast and efficient algorithms that can handle large volumes of data becomes a challenging task due to the large databases. In this paper, we implement a parallel Apriori algorithm based on MapReduce, which is a framework for processing huge datasets on certain kinds of distributable problems using a large number of computers (nodes). The experimental results demonstrate that the proposed algorithm can scale well and efficiently process large datasets on commodity hardware. © 2012 IEEE.

关键词： MapReduce

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Secure Cooperative Spectrum Sensing based on the Distance between Bodies of Evidence

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International Journal of Communications, Network and System Sciences 2012年第1期5卷 66-71页

作者： Yi Wang Yanjun Hu Xiwen Tang Yingguan Wang Key Laboratory of Intelligent Computing and Signal Processing Ministry of Education Anhui University Key Laboratory of Wireless Sensor Network & Communication Shanghai Institute of Microsystem and Information Technolgy Chinese Academy of Sciences

In cognitive radio (CR) networks, unlicensed secondary users need to conduct spectrum sensing to gain access to a licensed spectrum band. And cooperation among CR users will solve the problems caused by multipath fading and shadowing. In this paper, we propose a multi-threshold method at local nodes to cope with noises of great uncertainty. Functions of distance between bodies of evidence are used at fusion centre to make synthetic judgment. To guarantee security which is an essential component for basic network functions, we will take selfish nodes into account which try to occupy channels exclusively. The proposed technique has shown better performance than conventional algorithms without increase the system overhead.

关键词： Cognitive Radio Spectrum Sensing Multiple Thresholds Energy Detection Evidence Theory

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Faceted Navigation on Text

Faceted Navigation on Text

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第8届语义知识与网络国际会议(2012 Eighth International Conference on Semanties,Knowledge and Grids )(SKG2012)

作者： Bei Xu Key Lab of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences Beijing 100080 China

This paper proposes a method which is not for summarization but for extracting multiple facets from a text according to the keyword sets representing readers’ interests,so that readers can obtain the interested facets and carry out faceted navigation on text.A facet is a meaningful combination of the subsets of the *** text process technologies are mostly based on text features such as word frequency,sentence location,syntax analysis and discourse *** approaches neglect the cognition process of human *** proposed method considers human reading *** show that the facet extraction is effective and robust.

关键词： Semantics Humans Robustness Navigation Feature extraction Drugs information processing

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Hierarchical Chunk-to-String Translation 12

Hierarchical Chunk-to-String Translation

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Annual meeting of the Association for Computational Linguistics

作者： Yang Feng Dongdong Zhang Mu Li Ming Zhou Qun Liu University of Sheffield Sheffield UK Microsoft Research Asia Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences

ISBN: (纸本)9781622761715

We present a hierarchical chunk-to-string translation model, which can be seen as a compromise between the hierarchical phrase-based model and the tree-to-string model, to combine the merits of the two models. With the help of shallow parsing, our model learns rules consisting of words and chunks and meanwhile introduce syntax cohesion. Under the weighed synchronous context-free grammar defined by these rules, our model searches for the best translation derivation and yields target translation simultaneously. Our experiments show that our model significantly outperforms the hierarchical phrase-based model and the tree-to-string model on English-Chinese Translation tasks.

关键词：

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${\rm S}^{3}{\rm MKL}$: Scalable Semi-Supervised Multiple Kernel Learning for Real-World Image Applications

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IEEE Transactions on Multimedia 2012年第4期14卷 1259-1274页

作者： Shuhui Wang Qingming Huang Shuqiang Jiang Qi Tian Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Department of Computer Science University of Texas-San Antonio San Antonio TX USA

We study the visual learning models that could work efficiently with little ground-truth annotation and a mass of noisy unlabeled data for large scale Web image applications, following the subroutine of semi-supervised learning (SSL) that has been deeply investigated in various visual classification tasks. However, most previous SSL approaches are not able to incorporate multiple descriptions for enhancing the model capacity. Furthermore, sample selection on unlabeled data was not advocated in previous studies, which may lead to unpredictable risk brought by real-world noisy data corpse. We propose a learning strategy for solving these two problems. As a core contribution, we propose a scalable semi-supervised multiple kernel learning method (S 3 MKL) to deal with the first problem. The aim is to minimize an overall objective function composed of log-likelihood empirical loss, conditional expectation consensus (CEC) on the unlabeled data and group LASSO regularization on model coefficients. We further adapt CEC into a group-wise formulation so as to better deal with the intrinsic visual property of real-world images. We propose a fast block coordinate gradient descent method with several acceleration techniques for model solution. Compared with previous approaches, our model better makes use of large scale unlabeled images with multiple feature representation with lower time complexity. Moreover, to address the issue of reducing the risk of using unlabeled data, we design a multiple kernel hashing scheme to identify the “informative” and “compact” unlabeled training data subset. Comprehensive experiments are conducted and the results show that the proposed learning framework provides promising power for real-world image applications, such as image categorization and personalized Web image re-ranking with very little user interaction.

关键词： Kernel Visualization Training Data models Noise measurement Training data Learning systems

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Density based Collective Spatial keyword Query

Density based Collective Spatial Keyword Query

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第8届语义知识与网络国际会议(2012 Eighth International Conference on Semanties,Knowledge and Grids )(SKG2012)

作者： Li Zhang Xiaoping Sun Hai Zhuge Knowledge Grid Lab Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China

Geographic objects with descriptive text are gaining in prevalence in many web services such as Google *** keyword query which combines both the location information and textual description stands out in recent *** works mainly focus on finding top-k Nearest Neighbours where each node has to match the whole querying keywords.A collective query has been proposed to retrieve a group of objects nearest to the query object such that the group's keywords cover query's keywords and has the shortest inner-object *** the previous method does not consider the density of data objects in the spatial *** practice,a group of dense data objects around a query point will be more interesting than those sparse data *** distance of data objects of a group cannot reflect the density of the *** overcome this shortage,we proposed an approximate algorithm to process the collective spatial keyword query based on density and inner *** empirical study shows that our algorithm can effectively retrieve the data objects in dense areas.

关键词： Indexes Spatial databases Approximation algorithms Clustering algorithms Communities Query processing Semantics

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Mechanism of concept learning in topologized knowledge granular space based on GrC

Mechanism of concept learning in topologized knowledge granu...

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IEEE International Conference on Granular computing (GRC)

作者： Zuqiang Meng Zhongzhi Shi Shimo Shen College of Computer Electronics and Information Guangxi University Nanning China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Concept learning in information systems is actually performed in knowledge granular space on information systems. But no much attention has been paid to study such a knowledge granular space and its structure so far, and its structure characteristics are still poorly understood. In this paper, the granular space is firstly topologized and is decomposed into granular worlds. Then it is modeled as a bounded lattice. Finally, by using graph theory, the bounded lattice obtained is expressed as a hass graph, and the mechanism of concept learning in information systems can be visually explained. With related properties of topological space, bounded lattice and graph theory, the "mysterious" granular space can be delved more deeply into. This work can form a basis for designing concept learning algorithm as well as can richen the theory system for granular computing.

关键词： Computational modeling Iron Lattices Ice

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