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Emotion modeling in autonomic computing

Emotion modeling in autonomic computing

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2009 8th IEEE International Conference on cognitive Informatics, ICCI 2009

作者： Donglei, Zhang Pan, Yu Shil, Zhongzhi 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

ISBN: (纸本)9781424446421

Autonomic unit is the essential element and the most basic component of autonomic systems. Having the ability of handling emotions is considered to make autonomic unit more intelligent, more communicative and more social. In this article we try to build an emotion model for agents that act as autonomic units in autonomic systems and can self-manage its behavior to achieve the best performance. From four levels we define four models progressively and the top-level model is defined on the foundation of the three below, combining them as a unity. By given arousing axioms theoretically of several typical emotions, the model is proved to be effective for reasoning emotions of autonomic unit, and can be easily extended for dealing with other type of emotions. On this base an architecture of emotional autonomic unit is described. An example shows that emotion plays an important role in intelligent decision making, which proves the validity of the model and the special function in practice. © 2009 IEEE.

关键词： Decision making

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Multi-Agent Based Bioinformatics Integration Using Distributed Dynamic Description Logics

Multi-Agent Based Bioinformatics Integration Using Distribut...

引用

Fifth International Conference on Semantics,Knowledge and Grid(第五届语义、知识与网格国际会议 SKG 2009)

作者： Zhuxiao Wang Dapeng Zhang Zhongzhi Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Acad Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Acad

Integration of bioinformatics data repositories is a challenging task in which data sets are usually heterogeneous in structure and are often distributed across multiple, autonomously maintained databases. In this context, we present an innovative system which coordinates bioinformatics data by combining P2P data integration paradigm and Distributed Dynamic Description Logics (D3L) on top of Multi- Agent System infrastructure. We define the semantics and syntax of D3L, and propose a distributed consistency checking algorithm for realizing the intelligent query with logical reasoning function and decomposing large tasks to sub-tasks that could be tackled by different agents. Finally, we introduce a prototype implementation and present its evaluation. The results indicate that the proposed approach achieves excellent robustness and satisfactory performance.

关键词： bioinformatics integration agent technology Distributed Dynamic Description Logics

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Complementary Relations and Their Concept Lattices in Relational Databases

Complementary Relations and Their Concept Lattices in Relati...

引用

Fifth International Conference on Semantics,Knowledge and Grid(第五届语义、知识与网格国际会议 SKG 2009)

作者： Yuxia Lei Yuefei Sui Cungen Cao Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Acad Key Laboratory of Intelligent Information Processing Institute of Computing Technology CAS Beijing

The storage of data is a key issue of information systems, which is an important foundation for data query and data mining. Relational database model has been proven to be a very useful data-storage technique. As information is stored as data in relational databases, the induction of concepts from data is a pivotal topic in the data mining field. Formal Concept Analysis (FCA) turns out to be a perfect instrument for a meaningful and conceptual exploration of the stored data. In FCA, conceptual scaling provides a complete framework for transforming any many-valued context (i.e., relation/table) into a context (called a derived context), in which each manyvalued attribute is given a scale. The attributes in a scale basically describe meaningful features of the values of the initial attribute. From the logical point of view, complement operation plays a very important role in relational databases and data query systems. In this paper, we provide the connections between the concepts of binary relations and those of complementary binary relations, and propose an approach toward normalizing (complementary) scales, i.e., each (complementary) scale can be represented by a set of statements. One advantage of normalizing scales is to avoid generating huge derived relations, and hence this approach reduces storage cost. By the normalization, the concept lattice of the complement of a derived relation is reduced to a combination of the concept lattice of the derived relation and a set of statements.

关键词： relational databases complementary relations concept lattices normalized scales

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The Logical Operations on Relations, Scales and Concept Lattices

The Logical Operations on Relations, Scales and Concept Latt...

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Fifth International Conference on Semantics,Knowledge and Grid(第五届语义、知识与网格国际会议 SKG 2009)

作者： Yuxia Lei Cungen Cao Yuefei Sui Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Acad Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Acade

Object-attribute-value-relationships, which are a frequently used data structure to code real-world problems, are formalized via many-valued contexts in Formal Concept Analysis (FCA). The aim of FCA is to explore (formal) concepts from empirical data contexts. A concept of a context consists of two parts: the extent (objects the concept covers) and the intent (attributes describing the concept). From the logical point of view, the intent of each concept is a conjunction of some attributes. Similar to conjunction, negation and disjunction are also important logical operations of attributes or attributevalue pairs, which are common in human language. However, the classical FCA as a mathematical theory of concepts lacks a theory of negation and disjunction. In this paper, we take negation and disjunction into consideration in the process of constructing concepts, and hence obtain the following extended concepts: negative concepts of a context (i.e., a binary relation), negative concepts of a relation with some scales, V-concepts of a relation, V-concepts of a relation with some scales, logical concepts of a relation, and logical concepts of a relation with some scales. Compared with concepts in the classical FCA, the extended concepts mentioned above are more pertinent and more meaningful.

关键词： relational databases concept lattices logical operations negation disjunction conjunction

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CoBoost learning of visual categories with 1st and 2 nd order features from Google images 09

CoBoost learning of visual categories with 1st and 2 nd orde...

引用

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

作者： Liu, Xi Shi, Zhiping Li, Zhixin Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9781605586083

Conventional object recognition techniques rely heavily on manually annotated image datasets to achieve good performances. However, collecting high quality datasets is really laborious. In this paper, we propose a semi-supervised framework for learning visual categories from Google Images. The 1st and 2nd order features, which define bag of words representation and spatial relationship between local features respectively, make up an independent and redundant feature split. We then integrate a cotraining algorithm CoBoost with these two features. We create two boosting classifiers based on the 1st and 2nd order features respectively in the training, during which one classifier provides labels for the other. Besides, the 2nd order features are generated dynamically rather than extracted exhaustively to avoid high computation. An active learning technique is also introduced to further improve the performance. We evaluate our method on the benchmark datasets, showing results competitive with the state-of-the-art unsupervised approaches and some supervised techniques. Copyright 2009 ACM.

关键词： Object recognition

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A probabilistic model for automatic image annotation and retrieval

A probabilistic model for automatic image annotation and ret...

引用

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

作者： Li, Zhixin Ma, Huifang Shi, Zhiping Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University of Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9780769538365

Automatic image annotation has become an important and challenging problem due to the existence of the semantic gap. In this paper, we present an approach based on probabilistic latent semantic analysis (PLSA) to achieve the task. In order to model training data precisely, an image is firstly represented as a bag of visual words, then a probabilistic structure with two PLSA models is employed to capture semantic information from visual and textual modalities respectively. Furthermore, an adaptive asymmetric learning approach is proposed to fuse the aspects of these two models. For each image document, the distribution over aspects of different models is fused by multiplying different weights, which are determined by the entropy of the feature distribution. Consequently, the two models are linked with the same distribution over all aspects. This structure can predict semantic annotation well for an unseen image because it associates visual and textual modalities properly. We compare our approach with several previous approaches on a standard Corel dataset. The experimental results show that our approach performs more effectively and accurately. © 2009 IEEE.

关键词： Image retrieval

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Detecting unusual pattern with labeled data in two-stage

Detecting unusual pattern with labeled data in two-stage

引用

6th International Conference on Fuzzy Systems and Knowledge Discovery, FSKD 2009

作者： Li, Jincheng He, Qing Shi, Zhongzhi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100190 China

ISBN: (纸本)9780769537351

More analysis has been done to discover the meaningful unusual patterns which may mean fraud or anomaly. In this paper, a two-stage approach considering the labeled data is proposed to discover meaningful unusual observation, without the goal of classifying. We firstly apply Hyper Surface Classification (HSC) algorithm to gain a separating hyper surface which includes several pieces. Observation in the sparse piece is viewed as the unusual pattern. For other pieces with local density, we construct a weighted graph for it and search the Minimum Spanning Tree (MST), then detect further by cutting off several edges with the maximum weight. Combining the advantages of the two stages, a process of subdividing is proposed to consider the domain knowledge. Experimental results show that our approach can detect unusual pattern effectively together with other hidden valuable knowledge. © 2009 IEEE.

关键词： Trees (mathematics)

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Learning image semantics with latent aspect model

Learning image semantics with latent aspect model

引用

2009 IEEE International Conference on Multimedia and Expo, ICME 2009

作者： Zhixin, Li Xi, Liu Zhiping, Shi Zhongzhi, Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9781424442911

Automatic image annotation has become an important and challenging problem due to the existence of semantic gap. In this paper, we present an approach based on probabilistic latent semantic analysis (PLSA) to accomplish the tasks of semantic image annotation and retrieval. In order to model training images precisely, we employ two PLSA models to capture semantic information from visual and textual modalities respectively. Then an adaptive asymmetric learning approach is proposed to fuse aspects which are learned from both modalities. For each image document, the weight of each modality is determined by its contribution to the content of the image. Consequently, the two models are linked with the same distribution over aspects. This structure can predict semantic annotation for an unseen image because it associates visual and textual modalities properly. Finally, we compare our approach with several previous approaches on a standard Corel dataset. The experiment results show that our approach performs more effective and accurate. ©2009 IEEE.

关键词： Image retrieval

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Filter object categories: Employing visual consistency and semi-supervised approach

Filter object categories: Employing visual consistency and s...

引用

2009 IEEE International Conference on Multimedia and Expo, ICME 2009

作者： Xi, Liu Zhixin, Li Zhiping, Shi Zhongzhi, Shi Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China Graduate University Chinese Academy of Sciences Beijing 100049 China

ISBN: (纸本)9781424442911

We describe a method for filtering object category from a large number of noisy images. This problem is particularly difficult due to the greater variation within object categories and only a few labeled object images available. Our method deals with it by using visual consistency and semi-supervised approach. The images of one category often share some visual consistency so that the most irrelevant images can be first removed. Among the left images, a voting method is used to obtain more object exemplars with the initial object exemplars manually selected by users. Finally with all the obtained exemplars and those unlabeled images, we create a semi-supervised classifier to rank all the images. We evaluate our method on Berg dataset and demonstrate the precision comparative to the state-of-the-art. Besides, we collect five more categories from Google Images to show the effectiveness of the method. ©2009 IEEE.

关键词： Bandpass filters

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Reducing SMT rule table with monolingual key phrase 47

Reducing SMT rule table with monolingual key phrase

引用

Joint Conference of the 47th Annual Meeting of the Association for Computational Linguistics and 4th International Joint Conference on Natural Language processing of the AFNLP, ACL-IJCNLP 2009

作者： He, Zhongjun Meng, Yao Lü, Yajuan Yu, Hao Liu, Qun Fujitsu R and D Center CO. LTD Beijing China Key Laboratory of Intelligent Information Processing Institute of Computing Technology Chinese Academy of Sciences Beijing China

ISBN: (纸本)9781617382581

This paper presents an effective approach to discard most entries of the rule table for statistical machine translation. The rule table is filtered by monolingual key phrases, which are extracted from source text using a technique based on term extraction. Experiments show that 78% of the rule table is reduced without worsening translation performance. In most cases, our approach results in measurable improvements in BLEU score. © 2009 ACL and AFNLP.

关键词： Machine translation

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