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2012 International Conference on machine Learning and Cybernetics, ICMLC 2012

作者： Wang, Xiao-Lin Zhao, Hai Lu, Bao-Liang Center for Brain-Like Computing and Machine Intelligence Department of Computer Science and Engineering Shanghai Jiao Tong University Shanghai 200240 China MOE-Microsoft Key Laboratory for Intelligent Computing and Intelligent Systems Shanghai Jiao Tong University 800 Dong Chuan Rd. Shanghai 200240 China

ISBN: (纸本)9781467314855

Given the vastness of Internet, search engines have to find not only relevant but also high-quality web pages to satisfy users' information need. At present, most quality assessing methods for web pages are based on link analysis and user feedbacks. Considering that users acquire information from web pages mainly through reading their text, this paper addresses automated quality assessment of web pages from textual content. This paper surveys related works on assessing text's quality, summarizes quality-related features, and examines them with a real-word data set. Experimental results show that features based on the length of text are the most effective, while combining length features with other features such as part-of-speech tags and readability can further improve the accuracy. © 2012 IEEE.

关键词： Websites

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Evaluating Relational Ranking Queries Involving Both Text Attributes and Numeric Attributes

Evaluating Relational Ranking Queries Involving Both Text At...

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Conference on computer science and Software Engineering(CSSE 2012)

作者： Liang Zhu Zhaoliang Xie Qin Ma Key Laboratory of Machine Learning and Computational Intelligence School of Mathematics and Computer ScienceHebei University Department of Foreign Language Teaching and Research Hebei University

In many database applications, ranking queries may reference both text and numeric attributes, where the ranking functions are based on both semantic distances/similarities for text attributes and numeric distances for numeric attributes. In this paper, we propose a new method for evaluating such type of ranking queries over a relational database. By statistics and training, this method builds a mechanism that combines the semantic and numeric distances, and the mechanism can be used to balance the effects of text attributes and numeric attributes on matching a given query and tuples in database search. The basic idea of the method is to create an index based on WordNet to expand the tuple words semantically for text attributes and on the information of numeric attributes. The candidate results for a query are retrieved by the index and a simple SQL selection statement, and then top-N answers are obtained. The results of extensive experiments indicate that the performance of this new strategy is efficient and effective.

关键词： Relational Database Ranking Query Semantic Distance Numeric Distance WordNet

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Chinese Keyword Search by Indexing in Relational Databases

Chinese Keyword Search by Indexing in Relational Databases

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Conference on computer science and Software Engineering(CSSE 2012)

作者： Liang Zhu Lijuan Pan Qin Ma Key Laboratory of Machine Learning and Computational Intelligence School of Mathematics and Computer ScienceHebei University Department of Foreign Language Teaching and Research Hebei University

In this paper, we propose a new method based on index to realize IR-style Chinese keyword search with ranking strategies in relational databases. This method creates an index by using the related information of tuple words and presents a ranking strategy in terms of the nature of Chinese words. For a Chinese keyword query, the index is used to match query search words and the tuple words in index quickly, and to compute similarities between the query and tuples by the ranking strategy, and then the set of identifiers of candidate tuples is generated. Thus, we retrieve top-N results of the query using SQL selection statements and output the ranked answers according to the similarities. The experimental results show that our method is efficient and effective.

关键词： Relational Database Chinese Keyword Search Index Ranking Strategy

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Guided mutation operation based on search degree and fitness estimation

Guided mutation operation based on search degree and fitness...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Liang Yin Jun Zhang Department of Computer Science Key Laboratory of Machine Intelligence and Sensor Network Ministry of Education Key Laboratory of Software Technology Education Department of Guangdong Sun Yat-sen University China

Mutation is a fundamental operation in genetic algorithm (GA) for it has a significant impact on global search ability and convergence rate. Traditional mutation operation of GA changes chromosomes randomly (or blindly), which would waste a lot of computational cost in searching less promising regions or those have been searched frequently. To address these drawbacks, this paper proposes a novel guide mutation. The proposed guide mutation makes use of history search experience to estimate the average fitness and search degree of sub-regions in the search space. New chromosomes generated by the guide mutation are more likely to be in regions with higher average fitness and less search degree. In this way, the search efficiency can be improved and the algorithm can have a stronger ability of jumping out of local optima. The proposed guide mutation is incorporated into a simple GA, forming a guided mutation GA (GMGA). The GMGA is validated by testing 23 benchmark functions and the experimental results reveal that the proposed guide mutation is very effective in improving the performance of GA.

关键词： Biological cells Genetic algorithms Convergence Sociology Statistics Equations Mathematical model

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A set-based discrete PSO for cloud workflow scheduling with user-defined QoS constraints

A set-based discrete PSO for cloud workflow scheduling with ...

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IEEE International Conference on Systems, Man and Cybernetics

作者： Wei-Neng Chen Jun Zhang Department of Computer Science Key Laboratory of Machine Intelligence and Sensor Network Ministry of Education Key Laboratory of Software Technology Education Department of Guangdong Province Sun Yat-sen University China

Cloud computing has emerged as a powerful computing paradigm that enables users to access computing services anywhere on demand. It provides a flexible way to implement computation-intensive workflow applications on a pay-per-use basis. Since users are more concerned on the satisfaction of Quality of Service (QoS) in cloud systems, the cloud workflow scheduling problem that addresses different QoS requirements of users has become an important and challenging problem for workflow management in cloud computing. In this paper, we tackle a cloud workflow scheduling problem which enables users to define various QoS constraints like the deadline constraint, the budget constraint, and the reliability constraint. It also enables users to specify one preferred QoS parameter as the optimization objective. A set-based PSO (S-PSO) approach is proposed for this scheduling problem. As the allocation of service instances can be regarded as the selection problem from a set of service instances, it is found the set-based representation scheme in S-PSO is natural for the considered problem. In addition, the S-PSO provides an effective way to take advantage of problem-based heuristics to further accelerate search. We define penalty-based fitness functions to address the multiple QoS constraints and integrate the S-PSO with seven heuristics. A discrete version of the comprehensive learning PSO (CLPSO) algorithm based on the S-PSO method is implemented. Experimental results show that the proposed approach is very competitive especially on the instances with tight QoS constraints.

关键词： Quality of service Reliability Optimization Cloud computing Processor scheduling Scheduling Minimization

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Chinese Keyword Search by Indexing in Relational Databases

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Journal of Software Engineering and Applications 2012年第12期5卷 107-112页

作者： Liang Zhu Lijuan Pan Qin Ma Department of Foreign Language Teaching and Research Hebei University Baoding Hebei 071002 China Key Laboratory of Machine Learning and Computational Intelligence School of Mathematics and Computer Science Hebei University Baoding Hebei 071002 China

关键词： Relational Database Chinese Keyword Search Index Ranking Strategy

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Evaluating Relational Ranking Queries Involving both Text Attributes and Numeric Attributes

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Journal of Software Engineering and Applications 2012年第12期5卷 88-93页

作者： Liang Zhu Zhaoliang Xie Qin Ma Department of Foreign Language Teaching and Research Hebei University Baoding Hebei 071002 China Key Laboratory of Machine Learning and Computational Intelligence School of Mathematics and Computer Science Hebei University Baoding Hebei 071002 China

关键词： Relational Database Ranking Query Semantic Distance Numeric Distance WordNet

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An Empirical Study on Influence of Approximation Approaches on Enhancing Fireworks Algorithm

An Empirical Study on Influence of Approximation Approaches ...

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IEEE International Conference on Systems, Man, and Cybernetics

作者： Yan Pei Shaoqiu Zheng Ying Tan Hideyuki Takagi Graduate School of Design Kyushu University Department of Machine Intelligence School of Electronics Engineering and Computer Science Peking University Key Laboratory of Machine Perception (Ministry of Education) Faculty of Design Kyushu University

ISBN: (纸本)9781467317139

This paper presents an empirical study on the influence of approximation approaches on accelerating the fireworks algorithm search by elite strategy. In this study, we use three sampling data methods to approximate fitness landscape, i.e. the best fitness sampling method, the sampling distance near the best fitness individual sampling method and the random sampling method. For each approximation methods, we conduct a series of combinative evaluations with the different sampling method and sampling number for accelerating fireworks algorithm. The experimental evaluations on benchmark functions show that this elite strategy can enhance the fireworks algorithm search capability effectively. We also analyze and discuss the related issues on the influence of approximation model, sampling method, and sampling number on the fireworks algorithm acceleration performance.

关键词： Fireworks Algorithm Elite Strategy Fitness Landscape Approximation Acceleration firework displays approximation sampling methods empirical studies Approximation method acceleration

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Simulation of tactile sensors using soft contacts for robot grasping applications

Simulation of tactile sensors using soft contacts for robot ...

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IEEE International Conference on Robotics and Automation (ICRA)

作者： Sami Moisio Beatriz León Pasi Korkealaakso Antonio Morales Centre of Computational Engineering and Integrated Design (CEID) at the Department of Machine Technology Lappeenranta University of Technology Lappeeranta Finland Robotic Intelligence Laboratory at the Department of Computer Science and Engineering Universitat Jaume I Castellon Spain

In the context of robot grasping and manipulation, realistic simulation requires accurate modeling of contacts between bodies and, in a practical level, accurate simulation of touch sensors. This paper addresses the problem of simulating a tactile sensor considering soft contacts and full friction description. The developed model consists of a surface contact patch described by a mesh of contact elements. For each element, a full friction description is built considering stick-slip phenomena. The developed sensor model is implemented using OpenRAVE and used to perform typical tasks related to tactile sensors. The performance of the simulated sensor is then compared to a real one. It is also demonstrated how it can be integrated on the simulation of a complete robot grasping system.

关键词： Tactile sensors Force Friction Grasping Geometry

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Robust and Dynamic Data Aggregation in Wireless Sensor Networks: A Cross-Layer Approach

Robust and Dynamic Data Aggregation in Wireless Sensor Netwo...

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Symposia and Workshops on Ubiquitous, Autonomic and Trusted Computing, UIC-ATC

作者： Weigang Wu Jiannong Cao Hejun Wu Jingjing Li The Key Laboratory of Machine Intelligence and Sensor Networks Ministry of Education China Department of Computer Science Sun Yat-sen University Guangzhou China Department of Computing Hong Kong Polytechnic University Hong Kong China

In-network data aggregation is an effective technique to reduce communication cost in wireless sensor networks. Recent works have focused on two issues individually: dynamic aggregation to handle irregular traffic of events and robust aggregation to tolerate packet losses. However, how to achieve both the objectives simultaneously is still not touched. In this paper, we propose a cross-layer approach to robust and dynamic data aggregation by making use of direct support from MAC layer. A new MAC protocol, DA-MAC is delicately designed to serve such purpose. Based on the channel contention information obtained from DA-MAC, a node can dynamically determine where and when to do aggregation. To cope with packet losses, a virtual overlay, Rings is adopted to forward one packet to multiple nodes. We have implemented our design in TinyOS based sensor networks. Performance evaluations though simulations and experiments show that, compared with existing algorithms, our proposed solution is more efficient in terms of both time and energy cost.

关键词： Heuristic algorithms Media Access Protocol Robustness Wireless sensor networks Algorithm design and analysis

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