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An Empirical Comparative Study on Two Large-Scale Hierarchical Text Classification Approaches

International Journal of computer Processing of Languages 2011年第4期23卷 309-325页

作者： JIAN ZHANG HAI ZHAO LIQING ZHANG BAO-LIANG LU Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiaotong University 800 Dongchuan Rd. Shanghai 200240 China Department of Computer Science Virginia Tech Blacksburg VA 24061 USA

Patent classification is a large scale hierarchical text classification (LSHTC) task. Though comprehensive comparisons, either learning algorithms or feature selection strategies, have been fully made in the text categorization field, few work was done for a LSHTC task due to high computational cost and complicated structural label characteristics. For the first time, this paper compares two popular learning frameworks, namely, hierarchical support vector machine (SVM) and k -nearest neighbor ( k -NN) that are applied to a LSHTC task. Our experimental results show that the latter outperforms the former for the LSHTC task, which is quite different from the existing results for normal text categorization tasks. In addition, this paper compares different similarity measures and ranking strategies in k -NN framework for LSHTC task. From our empirical study, conclusions can be drawn that k -NN is more appropriate for the LSHTC task than hierarchical SVM. BM25 outperforms other similarity measures and ListWeak gains a better performance than other ranking strategies. Our empirical results also indicate that using all the labels of the retrieved neighbors can remarkably improve classification performance over only using the first label of the retrieved neighbors.

关键词： Large-scale text classification hierarchical text classification text classification k -NN hierarchical SVM similarity measure ranking strategies

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Reports of the AAAI 2010 fall symposia

Reports of the AAAI 2010 fall symposia

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作者： Azevedo, Roger Biswas, Gautam Bohus, Dan Carmichael, Ted Finlayson, Mark A. Hadzikadic, Mirsad Havasi, Catherine Horvitz, Eric Kanda, Takayuki Koyejo, Oluwasanmi Lawless, William F. Lenat, Doug Meneguzzi, Felipe Mutlu, Bilge Oh, Jean Pirrone, Roberto Raux, Antoine Sofge, Donald A. Sukthankar, Gita Van Durme, Benjamin Yorke-Smith, Neil Department of Educational and Counseling Psychology McGill University Canada Center for Intelligent Systems Vanderbilt University United States Microsoft Research Redmond United States Department of Software and Information Systems University of North Carolina Charlotte United States Complex Systems Institute United States Computer Science and Artificial Intelligence Laboratory Massachusetts Institute of Technology United States Media Lab. Massachusetts Institute of Technology United States ATR Intelligent Robotics and Communication Laboratories Kyoto Japan Department of Electrical and Computer Engineering University of Texas Austin United States Department of Mathematics Paine College Augusta GA United States Cycorp Austin TX United States Robotics Institute Carnegie Mellon University United States Department of Computer Sciences University of Wisconsin Madison United States University of Palermo Italy Honda Research Institute United States Navy Center for Applied Research in Artificial Intelligence Naval Research Laboratory Washington DC United States Department of Electrical Engineering and Computer Science University of Central Florida United States Department of Computer Science Johns Hopkins University United States American University of Beirut Lebanon SRI International's Artificial Intelligence Center United States

The Association for the Advancement of Artificial Intelligence (AAAI) presented the 2010 Fall Symposium Series on November 11-13, 2010. The eight symposia included Cognitive and Metacognitive Educational systems, Commonsense Knowledge, Complex Adaptive systems: Resilience, Robustness, and Evolvability, Computational Models of Narrative, Dialog with Robots, Manifold Learning and Its Applications, Proactive Assistant Agents and Quantum Informatics for Cognitive, Social, and Semantic Processes. Cognitive and Metacognitive Educational systems aimed to provide a comprehensive definition of metacognitive educational systems that is inclusive of the theoretical, architectural, and educational aspects of this field. The AAAI Commonsense Knowledge Fall Symposium had the goal of bringing together the diverse elements of this community whose work benefits from or contributes to the representation of general knowledge about the world. One of the specific goals of Proactive symposium was to gather the researchers from various projects in assistant agents to share their wisdom in retrospect.

关键词： Semantics

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MIND: A black-box energy consumption model for disk arrays

MIND: A black-box energy consumption model for disk arrays

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International Green Computing Conference

作者： Zhuo Liu Jian Zhou Weikuan Yu Fei Wu Xiao Qin Changsheng Xie Key Laboratory of Data Storage Systems Ministry of Education Wuhan National Laboratory for Optoelectronics School of Computer Science and Technology Huazhong University of Science and Technology Wuhan Hubei China Department of Computer Science & Software Engineering Aubum University AL USA

Energy consumption is becoming a growing concern in data centers. Many energy-conservation techniques have been proposed to address this problem. However, an integrated method is still needed to evaluate energy efficiency of storage systems and various power conservation techniques. Extensive measurements of different workloads on storage systems are often very time-consuming and require expensive equipments. We have analyzed changing characteristics such as power and performance of stand-alone disks and RAID arrays, and then defined MIND as a black box power model for RAID arrays. MIND is devised to quantitatively measure the power consumption of redundant disk arrays running different workloads in a variety of execution modes. In MIND, we define five modes (idle, standby, and several types of access) and four actions, to precisely characterize power states and changes of RAID arrays. In addition, we develop corresponding metrics for each mode and action, and then integrate the model and a measurement algorithm into a popular trace tool - blktrace. With these features, we are able to run different IO traces on large-scale storage systems with power conservation techniques. Accurate energy consumption and performance statistics are then collected to evaluate energy efficiency of storage system designs and power conservation techniques. Our experiments running both synthetic and real-world workloads on enterprise RAID arrays show that MIND can estimate power consumptions of disk arrays with an error rate less than 2%.

关键词： Power measurement Benchmark testing Throughput

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Evaluation method with measureable space-time dynamic properties for mobile Ad Hoc networks

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Ruan Jian Xue Bao/Journal of software 2011年第6期22卷 1333-1349页

作者： Wang, Wei Guan, Xiao-Hong Wang, Bei-Zhan Wang, Ya-Ping State Key Laboratory for Manufacturing Systems Engineering Xi'an Jiaotong University Xi'an 710049 China School of Computer Science Xi'an Polytechnic University Xi'an 710048 China School of Software Xiamen University Xiamen 361005 China Department of Industrial and Systems Engineering Texas A and M University TX 77843 United States

Mobility model is a crucial feature to differentiate ad hoc networks from other networks. The evaluation of dynamic network properties caused by mobility model is the basic problem for research on protocol simulation and related technologies, such as topology control and network performance measurement, in ad hoc networks. In this paper, a model-based description of ad hoc networks is improved to avoid the drawbacks in describing the corresponding space-time dynamic properties. Then a universal evaluation method with measureable space-time dynamic properties is presented. The dynamic properties of several mobility models are studied by constructing the space distribution of the nodes and designing the models for analyzing the topological space-time dynamic properties. Furthermore, a novel mobility model based on circular curve movement is proposed to improve the flexibility and the capability to describe realistic scenarios with curve movement. Simulation with NS2 shows the presented method can effectively evaluate the characteristics of the existing mobility models. The numerical results also show that the proposed mobility model has good dynamic properties in comparison with the existing mobility models. ©2011 ISCAS.

关键词： Mobile ad hoc networks

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Computational Intelligence for Control of Wind Turbine Generators

Computational Intelligence for Control of Wind Turbine Gener...

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IEEE Power and Energy Society General Meeting

作者： Wei Qiao Jiaqi Liang Ganesh K. Venayagamoorthy Ronald Harley Department of Electrical Engineering University of Nebraska-Lincoln School of Electrical and Computer Engineering Georgia Institute of Technology Real-Time Power and Intelligent Systems Laboratory Missouri University of Science and Technology

ISBN: (纸本)9781457710001

This paper summarizes past and ongoing research in the area of the application of computational intelligence (CI) for control of wind turbine generators (WTGs). Several intelligent design approaches and control strategies, including optimal design of WTG controllers using particle swarm optimization (PSO) and mean-variance optimization (MVO) algorithms and adaptive critic design-based coordinated optimal adaptive control for wind plants and shunt FACTS devices, are presented for dynamic performance and fault ride-through enhancement of WTGs and the associated power grid. The effectiveness of these intelligent design approaches and control strategies are demonstrated by nonreal- and real-time simulations in PSCAD/EMTDC and RSCAD/RTDS, respectively.

关键词： Computational intelligence (CI) Doubly fed induction generator (DFIG) Dual heuristic programming (DHP) FACTS device Heuristic dynamic programming (HDP) Particle swarm optimization (PSO) Radial basis function neural network (RBFNN) Wind turbine Wind Generators Artificial Intelligence Computational intelligence Wind Energy Conversion systems Standing Orders intelligent Design design approach dynamic characteristics shunt Optimal design

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A trust model for capability delegation in federated policy systems

A trust model for capability delegation in federated policy ...

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International Conference on Risks and Security of Internet and systems, CRiSIS

作者： Kevin Feeney Simon N. Foley Rob Brennan FAME and Knowledge & Data Engineering Group Intelligent Systems Laboratory Trinity College Dublin Ireland FAME and Department of Computer Science University College Cork Cork Ireland

Federated policy systems are required to support the emergent complexity and organizational heterogeneity of modern Internet service delivery. This paper presents a distributed policy management approach which utilizes a flexible, tree-based capability authority model to partition and delegate federated capabilities or services. A trust management model and a delegation logic is defined which supports secure decentralized policy reasoning and addresses performance overheads due to distributed rule evaluation, threats from malformed or malicious federated principals and allows flexibility with respect to delegation chain reduction or capability authority re-partitioning. The system is evaluated through a security analysis and a prototype implementation of a federated policy engineering framework based on this logic is described. This framework is based on public key certificates and an extension to the Keynote Trust Management language. It provides practical management services such as key discovery and certificate revocation in addition to the core capability delegation function.

关键词： Information services Public key Internet Semantics Authorization Web and internet services

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A study of an irrelevant variability normalization based discriminative training approach for LVCSR

A study of an irrelevant variability normalization based dis...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Yu Zhang Jian Xu Zhi-Jie Yan Qiang Huo Department of Computer Science and Engineering Shanghai Jiaotong University Shanghai China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems China Microsoft Research Asia Beijing China University of Science and Technology Hefei China

This paper presents a discriminative training (DT) approach to irrelevant variability normalization (IVN) based training of feature transforms and hidden Markov models for large vocabulary continuous speech recognition. A speaker-clustering based method is used for acoustic sniffing and maximum mutual information (MMI) is used as a training criterion. Combined with unsupervised adaptation of feature transforms, the IVN-based DT approach achieves a 14.5% relative word error rate reduction over an MMI-trained baseline system on a Switchboard-1 conversational telephone speech transcription task.

关键词： Training Hidden Markov models Acoustics Transforms Speech Speech recognition Feature extraction

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The integration of skin color segmentation and self-adapted template matching for the robust face detection

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International Review on computers and software 2011年第5期6卷 795-805页

作者： Zhiwen, Wang Shao-Zi, Li Ying, Dai Cognitive Science Department Xiamen University Xiamen 361005 China Department of Computer and Engineering Guangxi University of Technology Liuzhou 545006 China Fujian Key Laboratory of the Brain-like Intelligent Systems Xiamen University Xiamen 361005 China Faculty of Software and Info. Science Iwate Pref. University Iwate Japan

In this paper, an approach of integrating skin color segmentation and self-adapted template matching for the robust face detection is proposed. According to the clustering properties of the skin color of human faces in the YCbCr color space, the regions which close to the skin color are separated from the image by using Gaussian mixture model in order to achieve the purpose of rapidly detecting the external face. The influence of the brightness on the detection of the human faces is eliminated by using the illumination compensation technology, and also the confusion of the regions with the closed skin color with the human face is overcome by the adaptive template matching. Computation in the matching process is reduced by using the second matching algorithm. Experimental results show that proposed method can rapidly detect the human faces from a variety of images, while those detected faces include several of facial images with the different sizes, poses, races under the different illumination conditions. © 2011 Praise Worthy Prize S.r.l. - All rights reserved.

关键词： Template matching

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Design of a robot cloud center

Design of a robot cloud center

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International Workshop on Assurance in Distributed systems and Networks

作者： Du, Zhihui Yang, Weiqiang Chen, Yinong Sun, Xin Wang, Xiaoying Xu, Chen Tsinghua National Laboratory for Information Science and Technology Department of Computer Science and Technology Tsinghua University 100084 Beijing China School of Software and Microelectronics Peking University 102600 Beijing China School of Computing Informatics and Decision Systems Engineering Arizona State University Tempe AZ 85287 United States Department of Computer Technology and Application Qinghai University Xining Qinghai 810016 China International School Beijing University of Posts and Telecommunications 102209 Beijing China

ISBN: (纸本)9780769543499

Service-oriented architecture and cloud computing have become the prevalent computing paradigm. In this paradigm, computing resources can be accessed like other utility services available in today's society. In the meantime, robotics applications are joining the trend. More and more robot applications are shifting from manufacture to non-manufacture and service industries. However, for the on-demand supply of the large-scale heterogeneous robots, It is still a problem have not yet been studied, including the fundamental management and efficiency issues in using of these resources. In this paper, we design a framework of "Robot Cloud Center" (RCC) following the general cloud computing paradigm to address the current limitations in capacity and versatility of robotic applications. In this framework, a robot can be provided as a service just like a public utility service so that everyone can access the powerful robotic services easily, efficiently, and cheaply. Based on a given scenario, a robot scheduling algorithm in RCC is proposed to take advantage of the heterogeneous robot resources to meet the end user's requirement with the minimum cost.

关键词： Robot programming

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Analyzing interaction communication networks in enterprises and identifying hierarchies

Analyzing interaction communication networks in enterprises ...

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IEEE Network science Workshop (NSW)

作者： Yi Wang Marios Iliofotou Michalis Faloutsos Bin Wu Department of Computer Science and Engineering University of California Riverside Riverside CA USA Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing China

With the proliferation of electronic modes of communication (e.g., e-mails, short messages), a group of people in an enterprise can form several distinct Communication Interaction Networks, or CINs for short. A CIN is essentially a graph representation of “who talks to whom” among a group of individuals. In this paper, we conduct an empirical study of two modern enterprises and focus on three main questions: (Q1) how CINs from the two enterprises look, (Q2) how employees use the different available communication modes within an enterprise, and (Q3) how much information we can extract regarding the roles of their participants. We address these questions using empirical CINs from the Enron Corporation and a communication provider, using information from the exchange of e-mails, phone-calls, and short messages (SMS). For Q1, we reveal the following key structural properties that are shared by all the CINs in our study: they have high edge density, high clustering coefficient, and close to zero assortativity coefficient. For Q2, we observe that employees have differences in how they use the various communication modes. This suggests that different CINs capture different behavioral properties within an enterprise. For Q3, we propose HumanRank, a method of ranking individuals based on their importance (e.g., CEOs having higher rank than ordinary employees) using only the interactions between them. Next, using HumanRank, we introduce an unsupervised and parameter-free algorithm that identifies hierarchies by separating managers from ordinary employees. Our algorithm achieves above 70% accuracy and outperforms the state-of-the-art.

关键词： Electronic mail Measurement Barium Complex networks Generators Data mining Correlation

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