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International Conference on Computer Science and Software Engineering, CSSE 2008

作者： Ding, Shifei Jin, Fengxiang School of Computer Science and Technology China University of Mining and Technology Xuzhou 221008 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100080 China College of Geoinformation Science and Engineering Shandong University of Science and Technology Qingdao 266510 China

ISBN: (纸本)9780769533360

Similarity Measure(PSM) is a kind of measurement that measure the size of similarity between two patterns, it plays a key role in the analysis and research of pattern recognition, machine learning, clustering analysis. This article will firstly study the current PSM theory, point out its application range;secondly, discuss the axiomatic theory of fuzzy likelihood measure, give the frequently-used algorithms of fuzzy likelihood measure that based on axiomatic theory;finally, advance a new kind of fuzzy likelihood function, then establish the Fuzzy Likelihood Measure(FLM) between two fuzzy sets, so as to describe the similar degree between two fuzzy sets. FLM theory not only enriches and improves the PLS theory, and also provides new research methods for the theory research such as pattern recognition, machine learning, clustering analysis and so on. © 2008 IEEE.

关键词： Fuzzy sets

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Focused Crawling with Heterogeneous Semantic information

Focused Crawling with Heterogeneous Semantic Information

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IEEE WIC ACM International Conference on Web Intelligence (WI)

作者： Rui Huang Fen Lin Zhongzhi Shi Chinese Academy of Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Focused crawlers selectively retrieve Web documents that are relevant to a predefined set of topics. To intelligently make predictions and decisions about relevant URLs and web pages, different topic models have been introduced to represent topic-specific knowledge. Yet it is difficult to support semantic interoperability among different models. Moreover, some manually specified additional semantic information, such as semantic markups and social annotations, could not be effectively used to improve crawling. This paper proposes to boost focused crawling with four kinds of semantic models and semantic information, including thesauruses, categories, ontologies, and folksonomies. A statistical semantic association model is proposed to integrate different semantic models, represent heterogeneous semantic information, and support semantic relevance computation. A focused crawling framework is developed which adopts both keyword based contents and different kinds of additional information for relevance prediction and ranking. Experiments show that the proposed model and framework effectively integrates heterogeneous semantic information for focused crawling.

关键词： Crawlers Web pages Uniform resource locators intelligent agent Computers Ontologies information processing Semantic Web information retrieval Predictive models

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Adaptive multiple feedback strategies for interactive video search

Adaptive multiple feedback strategies for interactive video ...

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2008 International Conference on Image and Video Retrieval, CIVR 2008

作者： Luan, Huanbo Zheng, Yantao Neo, Shi-Yong Zhang, Yongdong Lin, Shouxun Chua, Tat-Seng Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate School Chinese Academy of Sciences Beijing 100039 China School of Computing National University of Singapore Singapore 117590 Singapore

ISBN: (纸本)9781605580708

In this paper, we propose adaptive multiple feedback strategies for interactive video retrieval. We first segregate interactive feedback into 3 distinct types (recall-driven relevance feedback, precision-driven active learning and locality-driven relevance feedback) so that a generic interaction mechanism with more flexibility can be performed to cover different search queries and different video corpuses. Our system facilitates expert searchers to flexibly decide on the types of feedback they want to employ under different situations. To cater to the large number of novice users (non-expert users), an adaptive option is built-in to learn the expert user behavior so as to provide recommendations on the next feedback strategy, leading to a more precise and personalized search for the novice users. Experimental results on TRECVID news video corpus demonstrate that our proposed adaptive multiple feedback strategies are effective. Copyright 2008 ACM.

关键词： Behavioral research

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A Modified Soft-Decision Algorithm of V-BLAST Architecture

A Modified Soft-Decision Algorithm of V-BLAST Architecture

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International Conference on Wireless Communications, Networking and Mobile Computing (WiCom)

作者： Dongfeng Zhao Daoben Li Key Laboratory of Information Processing and Intelligent Technology Information Engineering School BUPT Beijing University of Posts and Telecommunications Beijing China

A method based on modified sphere-decoding to compute the soft-information for the V-BLAST architecture is deduced in this paper. The system bit error ratio (BER) and computation complexity are simulated and compared with the classical methods. Simulation indicates that the new methods can reduce the decoding complexity with negligible performance degradation.

关键词： Maximum likelihood decoding Computer architecture Receiving antennas Telecommunication computing Computational modeling Random variables Laboratories information processing Computer errors Bit error rate

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Two Types of LDPC Decoding Methods for Coded Cooperation

Two Types of LDPC Decoding Methods for Coded Cooperation

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The 4th International Conference on Wireless Communications, Networking and Mobile Computing(第四届IEEE无线通信、网络技术及移动计算国际会议)

作者： Dongfeng Zhao Daoben Li Key Laboratory of Information Processing and Intelligent Technology Information Engineering School BUPT (Beijing University of Posts and Telecommunications) Beijing China

In this paper, two decoding methods are proposed for coded cooperation using LDPC codes. A simple upper bound based on the union bound is introduced and the performance of these two methods is evaluated and compared b... 详细信息

关键词： Low Density Parity-Check Codes Coded Cooperation

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An Improved FCM algorithm for Color Image Segmentation

An Improved FCM algorithm for Color Image Segmentation

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International Conference on Innovative Computing, information and Control (ICICIC)

作者： Zou Kaiqi Wang Zhiping Hu Ming Key Laboratory of Information Science and Engineering Dalian University of Technology Dalian China Liaoning Key Laboratory of Intelligent Processing Dalian University of Technology Dalian China

In this paper, an improved fuzzy C-means clustering (IFCM) algorithm for color image segmentation is proposed to solve the problem of heavy calculating burden and the disadvantage that clustering performance is affected by initial cluster centers for FCM, which is simple and easy to implement in color Image segmentation. For one thing, the quick subtractive clustering (QSC) is used for getting initial cluster centers of the image data points. For another, the first component of color feature set discovered by Ohta is chosen as the one-dimensional eigenvector. In order to reduce the computational complexity, the mapping from pixel space to eigenvector space is used for modifying the object function. Furthermore, combined the two problems of cluster centers initialization and cluster validity goes research to find optimizing the number of clusters. Experiments show that the proposed algorithm has better effect and lower computational complexity on color image segmentation.

关键词： Image segmentation Clustering algorithms Color Algorithm design and analysis Image color analysis Indexes Classification algorithms

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Convergence property analysis for PSO based on cluster-degree

Convergence property analysis for PSO based on cluster-degre...

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2008 International Conference on Computational Intelligence and Security, CIS 2008

作者： Quansheng, Dou Zhijun, Yu Ping, Jiang Zhongzhi, Shi Yantai Dongfang Electronics Information Industry Group Co. Ltd. Yantai China School of Nursing Binzhou Medical University Yantai China School of Computer Science and Technology Shandong Institute of Business and Technology Yantai China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769535081

The concept of cluster-degree was put forward and distribute status of particle with different clusterdegree was studied. The reasonable parameters setting range based on cluster-degree was proposed. Under the direction of cluster-degree, many parameters which can get better searching results were found. So this paper is helpful for the choosing and adjustment of PSO parameters in practical application. © 2008 IEEE.

关键词： Convergence Computational intelligence Computer security information security information analysis Industrial electronics Computer industry Electronics industry Medical services Computer science

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Object-based image retrieval with attention analysis and spatial re-ranking

IFIP Advances in Information and Communication Technology

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IFIP Advances in information and Communication technology 2008年 288卷 118-128页

作者： Gao, Ke Lin, Shouxun Zhang, Yongdong Tang, Sheng Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Graduate University of the Chinese Academy of Sciences Beijing100080 China Key Laboratory of Intelligent Information Processing nstitute of Computing Technology Chinese Academy of Sciences Beijing100080 China

ISBN: (纸本)9780387876849

In this paper, a new method is proposed for object-based image retrieval. The user supplies a query object by selecting a region from a query image, and the system returns a ranked list of images that contain the same object, retrieved from a large image database. The main outcomes of this research are as follows: (1) An novel object-based image retrieval framework that integrates effective pre-treatment and re-ranking is presented, (2) a new feature filtration method based on attention analysis is proposed for pre-treatment, (3) to further improve object retrieval precision, we add an efficient spatial configuration model to rerank the primary retrieval result using Bag of Word method. Experimental results demonstrate the effectiveness of our method. © 2008, Springer New York LLC . All rights rserved.

关键词： Query processing

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Human reappearance detection based on on-line learning

Human reappearance detection based on on-line learning

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作者： Hu, Lei Wang, Yizhou Jiang, Shuqiang Huang, Qingming Gao, Wen Key Lab of Intelligent Information Processing Chinese Academy of Sciences Beijing 100080 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Graduate University Chinese Academy of Sciences Beijing 100049 China Institute of Digital Media Peking University Beijing 100871 China Key Lab of Machine Perception Peking University MOE China

ISBN: (纸本)9781424421756

Many video surveillance applications require detecting human reappearances in a scene monitored by a camera or over a network of cameras. This is the human reappearance detection (HRD) problem. Studying this problem is important for analyzing a surveillance scenario at semantic level. In this paper, we propose a novel online learning frameworkfor solving HRD problem. Both generative model and discriminative model are employed in this framework and a voting scheme is presented to fuse the decisions ofboth models for determining whether a just entered person is one of those who have shown up, i.e. whether a reappearance happens. Both models will be updated based on mistake-driven online learning strategy. Our experimental results show that the adopted online learning framework not only improves the reappearance detection accuracy but also achieves high robustness in various surveillance scenes. © 2008 IEEE.

关键词： Cameras

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Fast commercial detection based on audio retrieval

Fast commercial detection based on audio retrieval

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IEEE International Conference on Multimedia and Expo (ICME)

作者： Dan Zhao Xiangdong Wang Yueliang Qian Qun Liu Shouxun Lin Institute of Computing Technology Key Laboratory of Intelligent Information Processing Beijing China Chinese Academy of Sciences Beijing China

Automatic detection of commercials in digital multimedia material is a challenging task with many applications. This paper presents a novel approach to fast commercial detection based on audio retrieval. It is based on the idea of segmenting energy envelope of audio into units, using only audio signal for matching on a commercial database. Fast searching and matching can be performed with high accuracy, by searching and by novel similarity function based on units. Experimental results show that 96.8% recall rate and 98.7% precision rate can be achieved under 0.125 real-time.

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