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The correspondence between the concepts in description logics for contexts and formal concept analysis

Science China(information Sciences) 2012年第5期55卷 1106-1122页

作者： MA Yue 1,2,SUI YueFei 1 & CAO CunGen 1 1 Key Laboratory of intelligent information processing,institute of computing Technology,Chinese Academy of Sciences,Beijing 100190,China 2 Graduate University of Chinese Academy of Sciences,Beijing,China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Graduate University of Chinese Academy of Sciences Beijing China

Formal concept analysis (FCA) and description logic (DL) are meant to be formalizations of concepts.A formal concept in the former consists of its intent and extent,where the intent is the set of all the attributes shared by each object in the extent of the concept,and the extent is the set of all the objects sharing each property in the intent of the concept.A concept in the latter formalization is simply a concept name,the interpretation of which is a subset of a *** consider the correspondence between concepts in both formalizations,a multi-valued formal context must be represented both as a knowledge base and as a model of the DL for contexts,where concepts are decomposed into tuple concepts C,interpreted as a set of tuples and value concepts V,interpreted as a set of attribute-value *** show that there is a difference between the interpretation of concepts R.V /R.C and the Galois connection between the extent/intent of formal concepts in *** to the Galois connection,there should be concepts of the form + R.V and + R.C inter-preted in FCA,and hence the logical language L for DL is extended to be L + together with + as a constructor so that + R.V and + R.C are well-defined ***,according to the interpretation in DL there should be pseudo concepts in FCA so that the interpretation of concepts R.V /R.C is the extent/intent of pseudo *** correspondence between formal concepts and concepts in L +,and between pseudo concepts and concepts in L are presented in this paper.

关键词： description logic formal concept analysis concept attribute/role

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VAction: A Lightweight and Integrated VR Training System for Authentic Film-Shooting Experience 25

VAction: A Lightweight and Integrated VR Training System for...

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Proceedings of the 2025 CHI Conference on Human Factors in computing Systems

作者： Shaocong Wang Che Qu Minjing Yu Chao Zhou Yuntao Wang Yu-Hui Wen Yuanchun Shi Yong-Jin Liu Department of Computer Science and Technology Tsinghua University Beijing China Film & TV Technology Department Beijing Film Academy Beijing Beijing China College of Intelligence and Computing Tianjin University Tianjin China Human Computer Interaction Technology and Intelligent Information Processing Laboratory Institute of Software Chinese Acadamy of Sciences Beijing China School of Computer Science and Technology Beijing Jiaotong University Beijing China Department of Computer science and Technology Tsinghua University Beijing China Computer Science and Technology Tsinghua University Beijing Beijing China

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Effectively Discriminating Fighting Shots in Action Movies

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Journal of Computer Science & Technology 2011年第1期26卷 187-194页

作者：马述高王伟强 School of Information Science and Engineering Graduate University of Chinese Academy of Sciences Computer Science Department Boston UniversityBoston MA 02215U.S.A. Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences

Fighting shots are the highlights of action movies and an effective approach to discriminating fighting shots is very useful for many applications, such as movie trailer construction, movie content filtering, and movie content retrieval. In this paper, we present a novel method for this task. Our approach first extracts the reliable motion information of local invariant features through a robust keypoint tracking computation; then foreground keypoints are distinguished from background keypoints by a sophisticated voting process; further, the parameters of the camera motion model is computed based on the motion information of background keypoints, and this model is then used as a reference to compute the actual motion of foreground keypoints; finally, the corresponding feature vectors are extracted to characterizing the motions of foreground keypoints, and a support vector machine （SVM） classifier is trained based on the extracted feature vectors to discriminate fighting shots. Experimental results on representative action movies show our approach is very effective.

关键词： video analysis motion concept learning

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Robust low-rank tensor factorization by cyclic weighted median

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Science China(information Sciences) 2015年第5期58卷 145-155页

作者： MENG DeYu ZHANG Biao XU ZongBen ZHANG Lei GAO ChenQiang Institute for Information and System Sciences and Ministry of Education Key Lab for Intelligent Networks and Network Security Xi'an Jiaotong University Department of Computing Hong Kong Polytechnic University Chongqing Key Laboratory of Signal and Information Processing Chongqing University of Posts and Telecommunications

Low-rank tensor factorization(LRTF) provides a useful mathematical tool to reveal and analyze multi-factor structures underlying data in a wide range of practical applications. One challenging issue in LRTF is how to recover a low-rank higher-order representation of the given high dimensional data in the presence of outliers and missing entries, i.e., the so-called robust LRTF problem. The L1-norm LRTF is a popular strategy for robust LRTF due to its intrinsic robustness to heavy-tailed noises and outliers. However, few L1-norm LRTF algorithms have been developed due to its non-convexity and non-smoothness, as well as the high order structure of data. In this paper we propose a novel cyclic weighted median(CWM) method to solve the L1-norm LRTF problem. The main idea is to recursively optimize each coordinate involved in the L1-norm LRTF problem with all the others fixed. Each of these single-scalar-parameter sub-problems is convex and can be easily solved by weighted median filter, and thus an effective algorithm can be readily constructed to tackle the original complex problem. Our extensive experiments on synthetic data and real face data demonstrate that the proposed method performs more robust than previous methods in the presence of outliers and/or missing entries.

关键词： tensor factorization low-rank weighted median filter tensorface

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The propositional normal default logic and the finite/infinite injury priority method

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Science China(information Sciences) 2017年第9期60卷 99-108页

作者： Wei LI Yuefei SUI Yuhui WANG State Key Laboratory of Software Development Environment Beihang University Key Laboratory of Intelligent Information Processing Institute of Computing TechnologyChinese Academy of Sciences School of Computer and Control Engineering University of Chinese Academy of Sciences

In propositional normal default logic, given a default theory(?, D) and a well-defined ordering of D, there is a method to construct an extension of(?, D) without any injury. To construct a strong extension of(?, D) given a well-defined ordering of D, there may be finite injuries for a default δ∈ D. With approximation deduction ?s in propositional logic, we will show that to construct an extension of(?, D) under a given welldefined ordering of D, there may be infinite injuries for some default δ∈ D.

关键词： default extension strong extension finite/infinite injury priority method recursively enumerable sets

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The B4-valued propositional logic with unary logical connectives ～1 /～2/┐

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Frontiers of Computer Science 2017年第5期11卷 887-894页

作者： Wei LI Yuefei SUI State Key Laboratory of Software Development Environment Beijing University of Aeronautics and Astronautics Beijing 100191 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

A B4-valued propositional logic will be proposed in this paper which there are three unary logical connectives ～1, ～2, ┐ and two binary logical connectives A, v, and a Gentzen-typed deduction system will be given s... 详细信息

关键词： the Belnap logic modality the soundness thecompleteness

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Discrete clothoid spline surfaces on open meshes

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International Journal of Image and Graphics 2001年第4期1卷 575-589页

作者： Li, Guiqing Li, Xianmin Li, Hua State Key Lab of CADandCG Zhejiang University Hangzhou310027 China Intelligent Information Processing Institute of Computing Technology Chinese Academic Sciences Beijing100080 China

By introducing a discrete Frenet frame, this paper first proposes 3D discrete clothoid splines to extend the planar discrete clothoid splines of Schneider and Kobbelt. On the basis of 3D discrete clothoid spline curves, discrete clothoid spline surfaces for arbitrary meshes are defined as a generalization of their closed discrete clothoid spline surfaces. Moreover, a discrete mean curvature normal operator instead of the conic surface fitting method is employed to compute curvature values. This induces a new iteration algorithm for generating the discrete clothoid spline surfaces. Since the curvature at a vertex is an area average over a region around this vertex and no linear system needs to be settled, the algorithm works more steadily and efficiently. Besides being directly used to produce fair mesh surfaces, the approach can also be employed to smooth control nets of spline surfaces. © 2001 World Scientific Publishing Company.

关键词： Linear systems

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Automatically organize web text resources with frequent term tree

Automatically organize web text resources with frequent term...

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IEEE 9th International Conference on Computer and information Technology, CIT 2009

作者： Wang, Xiaofeng Shi, Zhongzhi Key Lab. of Intelligent Information Processing Institute of Computing Technology Graduate University of Chinese Academy of Sciences Beijing China Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769538365

With the expansion of the Web, automatically organizing large scale text resources, e.g. Web pages, becomes very important. Many Web sites, like Google and Yahoo, use hierarchical classification trees to organize text resources in Web. User can easily find the text resources that meet their requirements by navigating these hierarchical classification trees. Typically, the text resources in Web are manually assigned to the nodes of the hierarchical classification tree. This limits the hierarchical classification tree to organize large scale text resources. In this paper, we propose a Frequent Term Tree to improve the ability of hierarchical classification tree in organizing large scale text resources in Web. Different from the Fp-tree [17] which is utilized to efficiently discover frequent patterns, the frequent term tree is used to organize resources with frequent pattern based classification. The Frequent Term Tree can accurately assign text resources to each node of classification tree and improve the ability in organizing resources with the incremental classified text resources. The evaluation of the Frequent Term Tree demonstrates that Frequent Term Tree can effectively and efficiently organize text resources. © 2009 IEEE.

关键词： Websites

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Plankton classification with deep convolutional neural networks

Plankton classification with deep convolutional neural netwo...

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2016 IEEE information Technology, Networking, Electronic and Automation Control Conference, ITNEC 2016

作者： Py, Ouyang Hong, Hu Zhongzhi, Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781467391924

Traditional methods for measuring and monitoring plankton populations are time consuming and can not scale to the granularity or scope necessary for large-scale studies. Improved approaches are needed. Manual analysis of the imagery captured by underwater camera system is infeasible. Automated image classification using machine learning tools is an alternative to the manual approach. In this paper, we present a deep neural network model for plankton classification which exploits translational and rotational symmetry. In this work, we propose two constrains in the design of deep convolutional neural network structure to guarantee the performance gain when going deep. Firstly, for each convolutional layer, its capacity of learning more complex patterns should be guaranteed;Secondly, the receptive field of the topmost layer should be no larger than the image region. We also developed a 'inception layer' like structure to deal with multi-size imagery input with convolutional neural network. The experimental result on Plankton Set 1.0 imagery data set show the feasibility and effectiveness of the proposed method. © 2016 IEEE.

关键词： Image classification

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Effectively constructing reliable data for cross-domain text classification

Effectively constructing reliable data for cross-domain text...

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

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

ISBN: (纸本)9783642328909

Traditional classification algorithms often fail when the independent and identical distributed (i.i.d.) assumption does not hold, and the cross-domain learning emerges recently is to deal with this problem. Actually, we observe that though the trained model from training data may not perform well over all test data, it can give much better prediction results on a subset of the test data with high prediction confidence. Also this subset of data from test data set may have more similar distribution with the test data. In this study, we propose to construct the reliable data set with high prediction confidence, and use this reliable data as training data. Furthermore, we develop an EM algorithm to refine the model trained from the reliable data. The extensive experiments on text classification verify the effectiveness and efficiency of our methods. It is worth to mention that the model trained from the reliable data achieves a significant performance improvement compared with the one trained from the original training data, and our methods outperform all the baseline algorithms. © 2012 IFIP International Federation for information processing.

关键词： Forecasting

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