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IEEE International Conference on Data Mining (ICDM)

作者： Changying Du Fuzhen Zhuang Qing He Zhongzhi Shi The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

Multi-task learning has proven to be useful to boost the learning of multiple related but different tasks. Meanwhile, latent semantic models such as LSA and LDA are popular and effective methods to extract discriminative semantic features of high dimensional dyadic data. In this paper, we present a method to combine these two techniques together by introducing a new matrix tri-factorization based formulation for semi-supervised latent semantic learning, which can incorporate labeled information into traditional unsupervised learning of latent semantics. Our inspiration for multi-task semantic feature learning comes from two facts, i.e., 1) multiple tasks generally share a set of common latent semantics, and 2) a semantic usually has a stable indication of categories no matter which task it is from. Thus to make multiple tasks learn from each other we wish to share the associations between categories and those common semantics among tasks. Along this line, we propose a novel joint Nonnegative matrix tri-factorization framework with the aforesaid associations shared among tasks in the form of a semantic-category relation matrix. Our new formulation for multi-task learning can simultaneously learn (1) discriminative semantic features of each task, (2) predictive structure and categories of unlabeled data in each task, (3) common semantics shared among tasks and specific semantics exclusive to each task. We give alternating iterative algorithm to optimize our objective and theoretically show its convergence. Finally extensive experiments on text data along with the comparison with various baselines and three state-of-the-art multi-task learning algorithms demonstrate the effectiveness of our method.

关键词： Semantics Optimization Feature extraction Data mining Data models Joints Iterative methods

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A multi-scale scheme for image segmentation using neuro-fuzzy classification and curve evolution

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Computer Aided Drafting,Design and Manufacturing 2012年第4期22卷 7-10页

作者： YUAN Da Key Laboratory of Intelligent Information Processing in Universities of Shandong(Shandong Institute of Business and Technology)

In this paper, we present a new scheme to segment a given image. This scheme utilizes neuro-fuzzy system to derive a proper set of contour pixels based on multi-scale images. We use these fuzzy derivatives to develop a new curve evolution model. The model automatically detect smooth boundaries, scaling the energy term, and change of topology according to the extracted con- tour pixels set. We present the numerical implementation and the experimental results based on the semi-implicit method. Experi- mental results show that one can obtains a high clualitv edge contour.

关键词： image filtering anisotropic diffusion diffusion function gradient threshold edge extract

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Rotation Estimation for Mobile Robot Based on Single-axis Gyroscope and Monocular Camera

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International Journal of Automation and computing 2012年第3期9卷 292-298页

作者： Yang, Ke-Hu Yu, Wen-Sheng Ji, Xiao-Qiang School of Mechanical Electronic and Information Engineering China University of Mining and Technology Beijing 100083 China Shanghai Key Laboratory of Trustworthy Computing East China Normal University Shanghai 200062 China State Key Laboratory of Intelligent Control and Management of Complex Systems Institute of Automation Chinese Academy of Sciences Beijing 100190 China

The rotation matrix estimation problem is a keypoint for mobile robot localization, navigation, and control. Based on the quaternion theory and the epipolar geometry, an extended Kalman filter (EKF) algorithm is proposed to estimate the rotation matrix by using a single-axis gyroscope and the image points correspondence from a monocular camera. The experimental results show that the precision of mobile robot s yaw angle estimated by the proposed EKF algorithm is much better than the results given by the image-only and gyroscope-only method, which demonstrates that our method is a preferable way to estimate the rotation for the autonomous mobile robot applications.

关键词： Rotation matrix estimation quaternion extended Kalman filter (EKF) monocular camera gyroscope.

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A novel online event analysis framework for micro-blog based on incremental topic modeling

A novel online event analysis framework for micro-blog based...

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

作者： Ma, Huifang Wang, Bo Li, Ning Department of Computer Science Northwest Normal University Lanzhou Gansu 730070 China Department of Military Information Management Shanghai Branch PLA Nanjing Institute of Politics Shanghai 200433 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences 100190 Beijing China

ISBN: (纸本)9780769547619

In this paper, we present a scalable implementation of a topic modeling (Adaptive Link-IPLSA) based method for online event analysis, which summarize the gist of massive amount of changing tweets and enable users to explore the temporal trends in topics. This model also can simultaneously maintain the continuity of the latent semantics to better capture the time line development of events. With the help of this model, users can quickly grasp major topics in these twitters. The preliminary results show that our method leads to more balanced and comprehensive improvement for online event detection compared to benchmark approaches. Additionally our algorithm is computationally feasible in near real-time scenarios making it an attractive alternative for capturing the rapidly changing dynamics of microblogs. © 2012 IEEE.

关键词： Semantics

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Parallel Web Mining System Based on Cloud Platform

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ZTE Communications 2012年第4期10卷 45-53页

作者： Shengmei Luo Qing He Lixia Liu Xiang Ao Ning Li Fuzhen Zhuang Pre-Research department of ZTE Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Graduate University of Chinese Academy of Sciences

Traditional machine-learning algorithms are struggling to handle the exceedingly large amount of data being generated by the internet. In real-world applications, there is an urgent need for machine-learning algorithms to be able to handle large-scale, high-dimensional text data. Cloud computing involves the delivery of computing and storage as a service to a heterogeneous community of recipients, Recently, it has aroused much interest in industry and academia. Most previous works on cloud platforms only focus on the parallel algorithms for structured data. In this paper, we focus on the parallel implementation of web-mining algorithms and develop a parallel web-mining system that includes parallel web crawler; parallel text extract, transform and load （ETL） and modeling; and parallel text mining and application subsystems. The complete system enables variable real-world web-mining applications for mass data.

关键词： web mining large scale high volume high dimension cloudcomputing

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PPLSA: Parallel probabilistic latent semantic analysis based on MapReduce 1

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7th IFIP International Conference on intelligent information processing, IIP 2012

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

ISBN: (数字)9783642328916

ISBN: (纸本)9783642328909

PLSA(Probabilistic Latent Semantic Analysis) is a popular topic modeling technique for exploring document collections. Due to the increasing prevalence of large datasets, there is a need to improve the scalability of computation in PLSA. In this paper, we propose a parallel PLSA algorithm called PPLSA to accommodate large corpus collections in the MapReduce framework. Our solution efficiently distributes computation and is relatively simple to implement. © 2012 IFIP International Federation for information processing.

关键词： MapReduce

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A Compact Difference Scheme for an Evolution Equation with a Weakly Singular Kernel

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Numerical Mathematics(Theory,Methods and Applications) 2012年第4期5卷 559-572页

作者： Hongbin Chen Da Xu Institute of Mathematics and Physics College of ScienceCentral South University of Forestry and TechnologyChangsha410004HunanChina Key Laboratory of High Performance Computing and Stochastic Information Processing(Ministry of Education of China) College of Mathematics and Computer ScienceHunan Normal UniversityChangsha410081HunanChina

This paper is concerned with a compact difference scheme with the truncation error of order 3/2 for time and order 4 for space to an evolution equation with a weakly singular *** integral term is treated by means of the second order convolution quadrature suggested by *** stability and convergence are proved by the energy method.A numerical experiment is reported to verify the theoretical predictions.

关键词： Evolution equation weakly singular kernel compact difference scheme stability convergence numerical experiment

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CROSS-MEDIA CLOUD computing

CROSS-MEDIA CLOUD COMPUTING

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2012 IEEE 2nd International Conference on Cloud computing and Intelligence Systems

作者： Zhongzhi Shi Guang Jiang Bo Zhang Jinpeng Yue Xiaofei Zhao Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences Graduate University of Chinese Academy of Sciences

Cross-media is the outstanding characteristics of the age of big data with large scale and complicated processing task. This article presents 5 issues and briefly summarizes the research progress of cross-media knowledge discovery. Furthermore, we propose a framework for cross-media semantic understanding which contains discriminative modeling, generative modeling and cognitive modeling. In cognitive modeling, a new model entitled CAM is proposed which is suitable for cross-media semantic understanding. Moreover, a Cross-Media intelligent Retrieval System (CMIRS) will be illustrated. In the final, the research directions and problems encountered are presented.

关键词： Cross-media Knowledge discovery Cloud computing CMIRS

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Leaf image recognition using Fourier transform based on ordered sequence

Leaf image recognition using Fourier transform based on orde...

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8th International Conference on intelligent computing technology, ICIC 2012

作者： Yang, Li-Wei Wang, Xiao-Feng Department of Automation University of Science and Technology of China Hefei Anhui 230027 China Intelligent Computing Laboratory Hefei Institute of Intelligent Machines Chinese Academy of Sciences P.O. Box 1130 Hefei Anhui 230031 China Key Lab. of Network and Intelligent Information Processing Hefei University Hefei Anhui 230601 China

ISBN: (纸本)9783642315879

There are a number of leaf recognition methods, but most of them are based on Euclidean space. In this paper, we will introduce a new description of feature for the leaf image recognition, which represents the leaf contour with the ordered sequence. For a leaf image, points on the contour represent the most important information of the leaf. Thus, by extracting serial points of the leaf contour, the unique corresponding ordered sequence can be obtained for a contour. Then, we can compute the amplitude-frequency feature by performing the Discrete Fourier transform on the ordered sequence. Since the low-frequency part of the Fourier transform represents the global information and the high-frequency part the local details, we can adopt the amplitude-frequency feature for leaf image recognition. Experimental results on the famous Swedish library and ICL library show that the proposed feature is effective for leaf image recognition. © 2012 Springer-Verlag.

关键词： Image recognition

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Contracting of web services with constraint handling rules

Contracting of web services with constraint handling rules

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2012 IEEE 8th World Congress on Services, SERVICES 2012

作者： Chen, Ruoyu Liao, Lejian Fang, Zhi Beijing Eng. Res. Ctr. of High Vol. Language Information Processing and Cloud Computing Applications Multi-living-agent Information System Key Laboratory Beijing Institute of Technology Beijing 100081 China

ISBN: (纸本)9780769547565

In e-service environment, service contract is important for assurance of business interoperability and quality of services. Combining service contract and process model will facilitate analyzing service process and monitoring service execution. This paper proposes a service modeling approach consists of service contract and process model. Service contracts are used as service advertisement and service request in this approach. The operational semantics of service contract and process model are translated into Constraint Handling Rules(CHR) program by a compiler. Based on this approach, a concept named service contracting is defined as a phase between service discovery and execution, which checks the consistency of service advertisement and process model as well as the the applicability of services w.r.t. the consumer's capabilities. Further, constraint solver centered implementation is designed, the modeling and contracting of web services under this architecture is illustrated. © 2012 IEEE.

关键词： Web services

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