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International Workshop on knowledge Discovery and Data Mining (WKDD)

作者： Hua Yuan Yi Li Wenhui Li Kong Zhao Duo Wang Rongqin Yi Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education College of Computer Science and Technology Jilin University Changchun China School of Computer Science & Engineering Changchun University of Technology China Suzhou Top Institute of Information Technology Suzhou China

Geometric constraint problem can be transformed to an optimization problem which the objective function and constraints are non-convex functions. In this paper an evolutionary algorithm based on ant colony optimization algorithm and the immune system model is proposed to provide solution to the geometric constraints problem. In the new algorithm, affinity calculation process and pheromone trail lying is embedded to maintain diversity and carry out the global search and the local search in many directions rather than one direction around the same individual simultaneously. This new algorithm different with current optimization methods in that it gets the good solution by excluding bad solutions. The experimental results reported here will shed more light into how affects the hybrid algorithm's search power in solving geometric constraint problem.

关键词： Immune system Ant colony optimization Nonlinear equations knowledge engineering Computer science educational technology Evolutionary computation Data mining Laboratories Computer science education

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Unsupervised key-phrases extraction from scientific papers using domain and linguistic knowledge

Unsupervised key-phrases extraction from scientific papers u...

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International Conference on Digital Information Management (ICDIM)

作者： Mikalai Krapivin Maurizio Marchese Andrei Yadrantsau Yanchun Liang Department of Information Engineering and Computer Science University of Trento Italy Department of Computer Science Belarusian State University Minsk Belarus College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin University China

The domain of Digital Libraries presents specific challenges for unsupervised information extraction to support both the automatic classification of documents and the enhancement of userspsila navigation in the digital content. In this paper, we propose a combined use of machine learning techniques (i.e. Support Vector Machines) and Natural Language Processing techniques (i.e. Stanford NLP parser) to tackle the problem of unsupervised key-phrases extraction from scientific papers. The proposed method strongly depends on the robust structural properties of a scientific paper as well as on the lexical knowledge that we are able to mine from its text. For the experimental assessment we have use a subset of ACM papers in the Computer Science domain containing 400 documents. Preliminary evaluation of the approach shows promising result that improves - on the same data-set - on state-of-the-art Bayesian learning system KEA from a minimum 27% to a maximum 77% depending on KEA parameters tuning and specific evaluation set. Our assessment is performed by comparison with key-phrases assigned by human experts in the specific domain and freely available through ACM portal.

关键词： Data mining Software libraries Navigation Machine learning Support vector machines Support vector machine classification Natural language processing Robustness Computer science Bayesian methods

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A Heuristic Clustering Algorithm for Mining Communities in Signed Networks

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Journal of Computer Science & Technology 2007年第2期22卷 320-328页

作者：杨博刘大有 College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun 130012 China

Signed network is an important kind of complex network, which includes both positive relations and negative relations. Communities of a signed network are defined as the groups of vertices, within which positive relations are dense and between which negative relations are also dense. Being able to identify communities of signed networks is helpful for analysis of such networks. Hitherto many algorithms for detecting network communities have been developed. However, most of them are designed exclusively for the networks including only positive relations and are not suitable for signed networks. So the problem of mining communities of signed networks quickly and correctly has not been solved satisfactorily. In this paper, we propose a heuristic algorithm to address this issue. Compared with major existing methods, our approach has three distinct features. First, it is very fast with a roughly linear time with respect to network size. Second, it exhibits a good clustering capability and especially can work well with complex networks without well-defined community structures. Finally, it is insensitive to its built-in parameters and requires no prior knowledge.

关键词： complex network signed network community clustering graph theory

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Genetic algorithm with local search for advanced planning and scheduling

Genetic algorithm with local search for advanced planning an...

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3rd International Conference on Natural computation, ICNC 2007

作者： Pu, Yan Dayou, Liu Donghui, Yuan Ji, Yu Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)0769528759

In this paper, a genetic algorithm approach with a novel mutation operator based on perturbation and local search has been proposed to solve an advanced planning and scheduling (APS) model in manufacturing supply chain, in which each customer order has a due date, each operation could be performed on alternative machines. The objective is to minimize the makespan of each customer order while ensuring the due date constraints. Various sizes of numerical experiments were carried out to demonstrate the efficiency of the proposed GA and the results indicate that the presented algorithm performs much better than previous work especially in large size problems. © 2007 IEEE.

关键词： Genetic algorithms

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Complex knowledge system modeling based on Hierarchical Fuzzy Petri Net

Complex knowledge system modeling based on Hierarchical Fuzz...

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2007 IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology - Workshops, WI-IAT Workshops 2007

作者： Hongjun, Pan Jigui, Sun Key Laboratory of Symbolic Computation and Knowledge Engineering Jilin University Ministry of Education Changchun 130012 China

ISBN: (纸本)0769530281

The difficulties of modeling complex knowledge system lie in a large quantity of knowledge rules and the difficulty in organizing rules and grasping their mutual logical relationships. This article proposed a concept of hierarchical fuzzy Petri nets (HFPN), which is more suitable for modeling complex knowledge system than other fuzzy Petri Net models. In addition, the concepts of abstract place and abstract transition in HFPN are allowed to describe and analyze the knowledge system at diverse abstract levels. Therefore, using HFPN, the iterative and incremental methods can be applied to modeling complex knowledge system. In addition, structured approach can be naturally applied to the process of modeling knowledge system. © 2007 IEEE.

关键词： Petri nets

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Recognizing the agent's goals incrementally:planning graph as a basis

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中国高等学校学术文摘·计算机科学 2007年第1期1卷 26-36页

作者： SUN Jigui YIN Minghao College of Computer Science Jilin UniversityChangchun 130012China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun 130012China College of Computer Science Jilin UniversityChangchun 130012China Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun 130012China College of Computer Northeast Normal UniversityChangchun 130024China

Plan recognition,the inverse problem of plan synthesis,is important wherever a system is expected to produce a kind of cooperative or competitive *** plan recognizers,however,suffer the problem of acquisition and hand-coding a larger plan *** paper is aims to show that modern planning techniques can help build plan recognition systems without suffering such ***,we show that the planning graph,which is an important component of the classical planning system Graphplan,can be used as an implicit,dynamic planning library to represent actions,plans and *** also show that modern plan generating technology can be used to find valid plans in this *** this sense,this method can be regarded as a bridge that connects these two research *** and theoretical results also show that the method is efficient and scalable.

关键词： Graphplan plan recognition constraints automated planning

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Inference and learning in hybrid probabilistic network

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中国高等学校学术文摘·计算机科学 2007年第4期1卷 429-435页

作者： WANG Limin WANG Xuecheng LI Xiongfei Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Jilin UniversityChangchun 130012China The Institute of Information Spreading Engineering Changchun University of TechnologyChangchun 130012China

This paper proposed a novel hybrid probabilistic network,which is a good tradeoff between the model complexity and learnability in *** relaxes the conditional independence assumptions of Naive Bayes while still permitting efficient inference and *** studies on a set of natural domains prove its clear advantages with respect to the generalization ability.

关键词： hybrid probabilistic network conditional independence assumption Bayesian network probabilistic neural network

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Flexible planning using fuzzy description logics

Flexible planning using fuzzy description logics

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2007 International Conference on Artificial Intelligence, ICAI 2007

作者： Shi, Lian Sun, Jigui Lu, Shuai Yin, Minghao College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun 130012 China

ISBN: (纸本)9781601320254

Description Logics are formalisms for representing knowledge of various domains in a structured and formally well-understood way. Typically, DLs are limited to dealing with precise and well defined concepts. In this paper we first present a fuzzy extension of ALC and define its syntax and semantics. Then we devote to taking advantage of the expressive power and reasoning capabilities of fuzzy ALC by encoding flexible planning problems within the framework of fuzzy ALC. Both theory and experimental results have shown that our method is sound and efficient.

关键词： Fuzzy logic

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Combinative reasoning with RCC5 and cardinal direction relations

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2nd International Conference on knowledge Science, engineering and Management, KSEM 2007

作者： Juan, Chen Dayou, Liu Changhai, Zhang Qi, Xie College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9783540767183

It is inadequate considering only one aspect of spatial information in practical problems, where several aspects are usually involved together. Reasoning with multi-aspect spatial information has become the focus of qualitative spatial reasoning. Most previous works of combing topological and directional information center on the combination with MBR based direction model or single-tile directions. The directional description is too approximate to do precise reasoning. Different from above, cardinal direction relations and RCC5 are introduced to represent directional and topological information. We investigate the mutual dependencies between basic relations of two formalisms, discuss the heterogeneous composition and give the detail composing rules. Then point out that only checking the consistency of topological and directional constraints before and after entailing by the constraints of each other respectively will result mistakes. Based on this, an improved constraint propagation algorithm is presented to enforce path consistency. And the computation complexities of checking the consistency of the hybrid constraints over various subsets of RCC5 and cardinal direction relations are analyzed at the end. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Information analysis

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Cardinal direction relations in 3D space

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2nd International Conference on knowledge Science, engineering and Management, KSEM 2007

作者： Juan, Chen Dayou, Liu Haiyang, Jia Changhai, Zhang College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University Changchun 130012 China

ISBN: (纸本)9783540767183

The existing 3D direction models approximate spatial objects either as a point or as a minimal bounding block, which decrease the descriptive capability and precision. Considering the influence of object's shape, this paper extends the planar cardinal direction (CD) into 3D space and obtains a new model called TCD (three-dimensional cardinal direction). Base on the smallest cubic TCD relations and original relations, explain the correlations between basic TCD relations and block algebra. Then according to the results in block algebra, two novel ways to compute the inverse and composition of basic TCD relations are proposed. And an O(n4) algorithm to check the consistency of a set of basic TCD constraints over simple blocks is given. © Springer-Verlag Berlin Heidelberg 2007.

关键词： Object recognition

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