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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 1. Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China2. Graduate University of Chinese Academy of Sciences Beijing 100049 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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Reasoning theory for D3L with compositional bridge rules 1

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

作者： Zhao, Xiaofei Tian, Dongping Chen, Limin Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China Research Institute of China Unicom Beijing China

ISBN: (数字)9783642328916

ISBN: (纸本)9783642328909

The semantic mapping in Distributed Dynamic Description Logics (D3L) allows knowledge to propagate from one ontology to another. The current research for knowledge propagation in D3L is only for a simplified case when only two ontologies are involved. In this paper we study knowledge propagation in more complex cases. We find in the case when more than two ontologies are involved and bridge rules form chains, knowledge does not always propagate along chains of bridge rules even if we would expect it. Inspired by Package-based description Logics, we extend the original semantics of D3L by imposing so called compositional consistency condition on domain relations in D3L interpretations. Under this semantics knowledge propagates along chains of bridge rules correctly. Furthermore we provide a distributed Tableaux reasoning algorithm for deciding satisfiability of concepts which is decidable in D3L under compositional consistency. Compared with original one, the extended D3L provides more reasonable logic foundation for distributed, dynamic system such as the information integration system and the Semantic Web. © 2012 IFIP International Federation for information processing.

关键词： Ontology

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Evaluating structure of complex networks by navigation entropy

Evaluating structure of complex networks by navigation entro...

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2012 8th International Conference on Semantics, Knowledge and Grids, SKG 2012

作者： Sun, Xiaoping Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769547947

Complex networks are extensively studied in various areas such as social networks, biological networks, Internet and WWW. Those networks have many characters such as small-diameter, higher cluster and power-law degree distribution. Small-world is evolved for efficient information transformation and navigation. Thus, navigation is an important functional character of networks. Previous researches mostly focus on understanding the navigability of small-world networks by analyzing the diameter and the routing efficiency. In this paper, we use the navigability to model the basic structural complexity of a network. That is, given a network topology, we need a model to evaluate how complex the topology is. Some network complexity models have been proposed but none of them consider the navigability factor of the network systems. We believe that using the navigability factor to evaluate the network structural complexity is a feasible and reasonable way. We use the adjacent matrix to build a navigation transition matrix and evaluate the randomness of random walks on the transition matrix by defining navigation entropy on it. We use the iteration of the random walk matrix to evaluate the navigability of a network and the complexity of network. That is, the higher the navigation entropy, the higher the randomness of a network. The lower the navigation entropy, the higher the structure of a network. We apply the navigation entropy model on a set of structural and random network topologies to show how the model can show the different complexity of networks. © 2012 IEEE.

关键词： Entropy

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Parallel decision tree with application to water quality data analysis 1

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9th International Symposium on Neural Networks, ISNN 2012

作者： He, Qing Dong, Zhi Zhuang, Fuzhen Shang, Tianfeng Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences China Graduate University of Chinese Academy of Sciences China

ISBN: (数字)9783642313622

ISBN: (纸本)9783642313615

Decision tree is a popular classification technique in many applications, such as retail target marketing, fraud detection and design of telecommunication service plans. With the information exploration, the existing classification algorithms are not good enough to tackle large data set. In order to deal with the problem, many researchers try to design efficient parallel classification algorithms. Based on the current and powerful parallel programming framework - MapReduce, we propose a parallel ID3 classification algorithm(PID3 for short). We use water quality data monitoring the Changjiang River which contains 17 branches as experimental data. As the data are time series, we process the data to attribute data before using the decision tree. The experimental results demonstrate that the proposed algorithm can scale well and efficiently process large datasets on commodity hardware. © 2012 Springer-Verlag.

关键词： MapReduce

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Theory for semantic relation computing and its application in semantic link network

Theory for semantic relation computing and its application i...

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2012 8th International Conference on Semantics, Knowledge and Grids, SKG 2012

作者： Sun, Yunchuan Lu, Cheng Yan, Hongli Bie, Rongfang Beijing Normal University Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9780769547947

Semantic relation among different objects is one of the most important kinds of semantics which plays the primary role for people and intelligent systems in grasping the situation accurately in the context of connected systems. The semantic relations are viewed as the most important elements in most existing information models (such as ER model, RDF and SLN) during the mapping from the physical world into the cyber world, where efficient ways of representation for semantic relations are developed. However, all these models deal with the semantic relations in a simple and intuitive way. Few works go deep into the study of semantic relations from a mathematic view. This paper aims at exploring a mathematic theory of the semantic relations between objects including representing methods, normal forms of operations, semantic orthogonal basis of the semantic relations. We also discuss the reasoning mechanism based on the proposed theory. The applications of the developed theory in semantic link network are discussed finally. © 2012 IEEE.

关键词： intelligent systems

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TINAC: A fast and effective web video topic detection framework

TINAC: A fast and effective web video topic detection framew...

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2012 9th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2012

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

ISBN: (纸本)9781467300223

Most of the previous works for web video topic detection(e.g., graph-based co-clustering method) always encounter the problem of real-time topic detection, since they all suffer from the high computation complexity. Therefore, a fast topic detection is needed to meet users' or administrators' requirement in real-world scenarios. Along this line, we propose a fast and effective topic detection framework, in which video streams are first partitioned into buckets using a time-window function, and then an incremental hierarchical clustering algorithm is developed, finally a video-based fusion strategy is used to integrate information from multiple modalities. Furthermore, a series of novel similarity metrics are defined in the framework. The experimental results on three months' YouTube videos demonstrate the effectiveness and efficiency of the proposed method. © 2012 IEEE.

关键词： Graphic methods

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Faceted navigation on text

Faceted navigation on text

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2012 8th International Conference on Semantics, Knowledge and Grids, SKG 2012

作者： Xu, Bei Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100080 China

ISBN: (纸本)9780769547947

This paper proposes a method which is not for summarization but for extracting multiple facets from a text according to the keyword sets representing readers' interests, so that readers can obtain the interested facets and carry out faceted navigation on text. A facet is a meaningful combination of the subsets of the text. Previous text process technologies are mostly based on text features such as word frequency, sentence location, syntax analysis and discourse analysis. These approaches neglect the cognition process of human reading. The proposed method considers human reading process. Experiments show that the facet extraction is effective and robust. © 2012 IEEE.

关键词： Navigation

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Effective comic-like representations with embedded regions of interest

Effective comic-like representations with embedded regions o...

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13th Pacific-Rim Conference on Multimedia, PCM 2012

作者： Herranz, Luis Liu, Huiying Jiang, Shuqiang Key Lab. of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642347771

Comic-like summaries exploit the narrative structure of comics to create intuitive and easily readable abstracts. However, real comics use complex composition techniques which are difficult to mimic in an unsupervised way as they involve high level semantic understanding. This paper explores the use of visual attention analysis and face detection to embed regions of interest in adjacent images, obtaining more compact yet informative representations. This paper also addresses the generation of the layout, which involves combinatorial optimization problems. In practice, using exhaustive search to solve the problem is not feasible due to the large number of images. A split and merge approach is proposed to effectively address the layout problem, thus the limitations of finding solutions in a wide range of row widths can be avoided. A user study conducted on several episodes of TV series confirmed the utility of the proposed approach. © 2012 Springer-Verlag.

关键词： Face recognition

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Ensemble of k-labelset classifiers for multi-label image classification

Ensemble of k-labelset classifiers for multi-label image cla...

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

作者： Zhang, Dapeng Liu, Xi Institute of Information Science and Engineering Yanshan University Qinhuangdao 066004 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9783642328909

In the real world, images always have several visual objects instead of only one, which makes it difficult for traditional object recognition methods to deal with them. In this paper, we propose an ensemble method for multi-label image classification. First, we construct an ensemble of k-labelset classifiers. A voting technique is then employed to make predictions for images based on the created ensemble of k-labelset classifiers. We evaluate our method on Corel dataset and demonstrate the precision, recall and F1 measure superior to the state-of-the-art methods. © 2012 IFIP International Federation for information processing.

关键词： Image classification

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A novel granular support vector machine based on mixed kernel function

International Journal of Digital Content Technology and its ...

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International Journal of Digital Content technology and its Applications 2012年第20期6卷 484-492页

作者： Huang, Huajuan Ding, Shifei Jin, Fengxiang Yu, Junzhao Han, Youzhen School of Computer Science and Technology China University of Mining and Technology Xuzhou 221116 China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Science Beijing 100080 China Beijing Key Laboratory of Intelligent Telecommunications Software and Multimedia Beijing University of Posts and Telecommunications Beijing 100876 China Geomatics College Shandong University of Science and Technology Qingdao 266510 China

The constaints of time and memory will reduce the learning performance of Support Vector Machine (SVM) when it is used to solve the large number of samples. In order to solve this problem, a novel algorithm called Granular Support Vector Machine based on Mixed Kernel Function (GSVM-MKF) is proposed. Firstly, the granular method is propsed and then the judgment and extraction methods of support vector particles are given. On the above basis, we propose a new granular support vector machine learning model. Secondly, in order to further improve the performance of the granular support vector machine learning model, a mixed kernel function which effectively uses the global kernel function having the good generalization ability and the local kernel function having good learning ability is proposed. Finally, the theoretical analysis and experimental results show the effectiveness of the method.

关键词： Support vector machines

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