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Collaborative filtering algorithm via compressing the sparse user-rating-data matrix

Xi'an Dianzi Keji Daxue Xuebao/Journal of Xidian University 2009年第4期36卷 614-618+638页

作者： Hou, Cui-Qin Jiao, Li-Cheng Zhang, Wen-Ge Ministry of Education Key Lab. of Intelligent Perception and Image Understanding Research Inst. of Intelligent Information Processing Xidian Univ. Xi'an 710071 China

The paper proposes a novel memory-based collaborative filtering algorithm-Multi-label Probabilistic Latent Semantic Analysis based Collaborative Filtering, which improves the quality of recommendations by reducing the dimension of the user-rating-data matrix by multi-label probabilistic latent semantic analysis when the matrix is extremely sparse. Firstly, it confines the set of latent variables of probability latent semantic analysis to the set of multi-label of items to make latent variables have meanings of corresponding labels. Then it learns the probabilistic distribution of latent variables, i.e., the model of use's interest, to compress the user-rating-data matrix. Finally, it computes the similarity between different users based on the above learned model and makes recommendations. Compared to memory-based collaborative filtering algorithms, the proposed algorithm decreases the mean absolute error 4 percents averagely on test dataset by reducing the dimension of the user-rating-data matrix. The proposed algorithm makes the recommendation system understandable and obtains competitive recommendations compared to the filtering algorithm which reduces the dimension of the user-rating-data matrix by probabilistic latent semantic analysis.

关键词： Iterative methods

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A new population diversity model in swarm intelligence

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Journal of information and Computational Science 2009年第4期6卷 1891-1898页

作者： Feng, Jiqiang Xie, Weixin Xu, Chen Huang, Jianjun Key Lab. for Intelligent Information Processing Shenzhen University Shenzhen 518060 China Institute of Intelligent Computing Science Shenzhen University Shenzhen 518060 China

Many researchers of swarm intelligence (SI) algorithms take their ideas from physical and biological systems. This approach, however, is mostly qualitative and many ideas remain vague and ill-defined. In this paper, a mathematical framework based on probability theory is presented that enables us to analyze one important aspect of SI algorithms: the population diversity. Firstly the population density is defined for the population in the SI algorithms. The population diversity is then discussed from the point of view of the normal distribution in statistics. We show that there is a close connection between the distribution and population diversity and that the essential structure of population diversity is quite similar to that of the distribution. A detailed construction of the population diversity model is then given that is based on probability distributions and the convergence of the model is theoretically discussed for single peak value case. The paper concludes with a generic numerical example that validates the population diversity model. © 2009 Binary information Press.

关键词： Normal distribution

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A compression algorithm for multi-streams based on GEP

A compression algorithm for multi-streams based on GEP

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3rd International Conference on Genetic and Evolutionary computing, WGEC 2009

作者： Ding, Chao Yuan, Chang-An Qin, Xiao Peng, Yu-Zhong Computer and Information Engineering College Guangxi Teachers Education University Nanning 530001 China First Middle School of Mengcheng Anhui Mengcheng233500 China Key Lab. of Scientific Computing and Intelligent Information Processing in Universities of Guangxi Guangxi Teachers Education University Nanning China

ISBN: (纸本)9780769538990

This paper applied the Methods which based on GEP in compress multi-streams. The contributions of this paper include: 1) giving an introduction to data function finding based on GEP(DFF-GEP), defining the main conception of Multi-Streams, and revealing the map relation in it;2) putting forward the Compression Algorithm for Multi-Streams according to map relation lied in data between data streams;and 3)providing an experience with the real data and find that (3.1) the compression ratio of the new methods is 120-150 times as the traditional wavelets method, and 35-70 times as the wavelets and coincidence method;(3.2) the relative error of the new method is about 3??,yet maximum relative error is 0.01 by using the traditional relative error standard, the precision is improved from 7% to 15% as compared with the traditional method. © 2009 IEEE.

关键词： Errors

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A generic approach to classify sports video shots and its application in event detection 09

A generic approach to classify sports video shots and its ap...

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1st International Conference on Internet Multimedia computing and Service, ICIMCS 2009

作者： Li, Lingfang Duan, Ling-Yu Huang, Qingming Du, Jun Gao, Wen Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Institute of Digital Media Peking University Beijing 100871 China Graduate University of Chinese Academy of Sciences Beijing 100190 China NEC Research Labs. China Beijing 100084 China

ISBN: (纸本)9781605588407

Shot type is useful information for semantic sports video analysis. Most existing approaches utilize predefined rules and domain knowledge to derive shot types in sports video. Although these methods have achieved promising results in some specific games, it is hard to extend them from one sport to another. To address this problem, we propose a generic approach to classify shots in sports video. Our approach utilizes bag of visual words model to represent key frame for each shot based on Scale Invariant Feature Transform (SIFT) feature points;either Support Vector Machine (SVM) or Probabilistic Latent Semantic Analysis (PLSA) are then employed to classify key frame to determine shot type. As our approach relies little on domain knowledge, it can be more easily extended to different sports. We have evaluated our shot classification approach over five types of sports video and have achieved promising results. To show the usefulness and effectiveness of our shot classification, we apply the results of shot type to detect events in basketball video via a generative-discriminative model. In addition, we have observed that some common visual parts frequently appear across various shots in the same sport or even different but relevant sports. For instance, soccer and basketball are relevant sports in the sense of field-ball game. Motivated by this observation, we attempt to alleviate the problem of insufficient sports video data in some applications by sharing these visual parts across different but relevant kinds of sports. Copyright 2009 ACM.

关键词： Sports

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Automatic adaptation of annotation standards: Chinese word segmentation and POS tagging: a case study 09

Automatic adaptation of annotation standards: Chinese word s...

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Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language processing of the AFNLP: Volume 1 - Volume 1

作者： Wenbin Jiang Liang Huang Qun Liu Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Google Research Charleston Rd. Mountain View CA

ISBN: (纸本)9781932432459

Manually annotated corpora are valuable but scarce resources, yet for many annotation tasks such as treebanking and sequence labeling there exist multiple corpora with different and incompatible annotation guidelines or standards. This seems to be a great waste of human efforts, and it would be nice to automatically adapt one annotation standard to another. We present a simple yet effective strategy that transfers knowledge from a differently annotated corpus to the corpus with desired annotation. We test the efficacy of this method in the context of Chinese word segmentation and part-of-speech tagging, where no segmentation and POS tagging standards are widely accepted due to the lack of morphology in Chinese. Experiments show that adaptation from the much larger People's Daily corpus to the smaller but more popular Penn Chinese Treebank results in significant improvements in both segmentation and tagging accuracies (with error reductions of 30.2% and 14%, respectively), which in turn helps improve Chinese parsing accuracy.

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Automatic sports genre categorization and view-type classification over large-scale dataset 09

Automatic sports genre categorization and view-type classifi...

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17th ACM International Conference on Multimedia, MM'09, with Co-located Workshops and Symposiums

作者： Li, Lingfang Zhang, Ning Duan, Ling-Yu Huang, Qingming Du, Jun Guan, Ling Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China Ryerson Multimedia Research Laboratory Ryerson University Toronto ON Canada Institute of Digital Media Peking University Beijing 100871 China Graduate University of Chinese Academy of Sciences Beijing 100190 China NEC Research Labs. China Beijing 100084 China

ISBN: (纸本)9781605586083

This paper presents a framework with two automatic tasks targeting large-scale and low quality sports video archives collected from online video streams. The framework is based on the bag of visual-words model using speeded-up robust features (SURF). The first task is sports genre categorization based on hierarchical structure. Following on the second task which is based on automatically obtained genre, views are classified using support vector machines (SVMs). As a consequence, the views classification result can be used in video parsing and highlight extraction. As compared with state-of-the-art methods, our approach is fully automatic as well as domain knowledge free and thus provides a better extensibility. Furthermore, our dataset consists of 14 sport genres with 6850 minutes in total. Both sport genre categorization and view type classification have more than 80% accuracy rates, which validate this framework's robustness and potential in web-based applications. Copyright 2009 ACM.

关键词： Support vector machines

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Fast car detection using image strip features

Fast car detection using image strip features

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Conference on Computer Vision and Pattern Recognition (CVPR)

作者： Wei Zheng Luhong Liang Graduate School of Chinese Academy of Sciences Beijing China Institute of Computing Technology Chinese Academy and Sciences Beijing China Key Lab of Intelligent Information Processing Chinese Academy of Sciences (CAS) Beijing 100190 China

This paper presents a fast method for detecting multi-view cars in real-world scenes. Cars are artificial objects with various appearance changes, but they have relatively consistent characteristics in structure that consist of some basic local elements. Inspired by this, we propose a novel set of image strip features to describe the appearances of those elements. The new features represent various types of lines and arcs with edge-like and ridge-like strip patterns, which significantly enrich the simple features such as haar-like features and edgelet features. They can also be calculated efficiently using the integral image. Moreover, we develop a new complexity-aware criterion for RealBoost algorithm to balance the discriminative capability and efficiency of the selected features. The experimental results on widely used single view and multi-view car datasets show that our approach is fast and has good performance.

关键词： Strips Face detection Object detection Biological system modeling Deformable models Computer vision Content addressable storage Support vector machines Humans Wheels

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An Approach for Diagnosing Unexpected Faults in Web Service Flows

An Approach for Diagnosing Unexpected Faults in Web Service ...

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International Conference on Grid and Cooperative computing (GCC)

作者： Xu Han Zhongzhi Shi Wenjia Niu Fen Lin Donglei Zhang Key Lab. of Intell. Inf. Process. Chinese Acad. of Sci. Beijing Beijing China The Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China

Potential faults have greatly reduced the dependability of business processes, so fault diagnosis is becoming an important issue which aims at supporting self-healing service flow execution. The existing fault handling mechanism provided by BPEL can only identify the faults which have been pre-defined in standards or by users. However, unexpected faults are also the main cause of failures in service flow execution. Therefore an effective diagnosis approach is needed to solve this problem. In this paper, we propose a logic-based approach for diagnosing unexpected faults in Web service flows. This approach uses dynamic description logic (DDL) to model business processes, and diagnoses faults based on DDL reasoning. We provide the DDL-based diagnosing algorithm, which takes process description and runtime information as inputs, and returns the related information of possible faults as the result. Moreover, to improve the efficiency of online diagnosis, the incremental DDL-based diagnosing algorithm is presented. Experimental results on a demo system show the effectiveness of this approach.

关键词： Web services Fault diagnosis Logic Grid computing laboratories information processing Computers Testing Runtime Engines

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A ROI quality adjustable rate control scheme for low bitrate video coding

A ROI quality adjustable rate control scheme for low bitrate...

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Picture Coding Symposium, PCS

作者： Ling Yang Li Zhang Siwei Ma Debin Zhao Chinese Academy of Sciences Beijing China Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy and Sciences Beijing China Institute of Digital Media School of Electronic Engineering and Computer Science Peking University Beijing China Department of Computer Science and Engineering Harbin Institute of Technology Harbin China

This paper proposed a novel Region of Interest (ROI) based rate control algorithm for video communication systems, in which the subjective quality of ROI can be adjusted according to users' requirements. In the proposed scheme, in order to analyze the relationship between subjective quality and encoding parameters, a structural similarity index map - quantization parameter (SSIM-QP) model is established. Through this relation, the possible visual quality range of ROI is defined according to the range of ROI QP, which is predicted by rate control algorithm. Then, with interest levels being identified within the visual quality range, resources allocated to ROI is determined. Finally, considering both the quality of ROI and the entire frame, resource allocation is slightly adjusted. Experimental results demonstrate that the subjective visual quality of ROI in our proposed scheme can be adjustable improved compared to the existing rate control algorithms.

关键词： Bit rate Video coding Quadratic programming Humans Computer science Quantization Resource management Videoconference PSNR Data mining

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Automatically discovering semantic links among documents

Automatically discovering semantic links among documents

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4th International Conference on Semantics, Knowledge, and Grid, SKG 2008

作者： Hai, Zhuge Junsheng, Zhang Key Lab of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing China

ISBN: (纸本)9780769534015

Knowing semantic links among documents is the basis for intelligent applications over large-scale document resources. Discovering these semantic links with little human interference is a challenge issue. This paper proposes an approach to automatically discover semantic links in document set based on a probabilistic documentary semantic link network model. The approach has the following advantages: 1) It supports probabilistic relational reasoning. 2) The semantic link networks and relevant rules automatically evolve. 3) It does not rely on any predefined ontology. 4) It can adapt to the update of the adopted techniques. Experiments on document sets of different types (scientific papers and Web pages) and different scales show the proposed approach feasible. The approach can be used to automatically construct semantic overlays on large document sets to support advanced applications like various relational queries on scientific documents. © 2008 IEEE.

关键词： Websites

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