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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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Combining Immune with Ant Colony Algorithm for Geometric Constraint Solving

Combining Immune with Ant Colony Algorithm for Geometric Con...

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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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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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Hilbert-huang transform-based local regions descriptors

Hilbert-huang transform-based local regions descriptors

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2007 18th British Machine Vision Conference, BMVC 2007

作者： Han, Dongfeng Li, Wenhui Guo, Wu Li, Zongcheng Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China School of Engineering Technology Shandong University of Technology Zibo China

ISBN: (纸本)1901725340

This paper presents a new interest local regions descriptors method based on Hilbert-Huang Transform. The neighborhood of the interest local region is decomposed adaptively into oscillatory components called intrinsic mode functions (IMFs). Then the Hilbert transform is applied to each component and get the phase and amplitude information. The proposed descriptors samples the phase angles information and amalgamates them into 10 overlap squares with 8-bin orientation histograms. The experiments show that the proposed descriptors are better than SIFT and other standard descriptors. Essentially, the Hilbert-Huang Transform based descriptors can belong to the class of phase-based descriptors. So it can provides a better way to overcome the illumination changes. Additionally, the Hilbert-Huang transform is a new tool for analyzing signals and the proposed descriptors is a new attempt to the Hilbert-Huang transform.

关键词： Hilbert-Huang transform

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An improved ant colony optimization algorithm based on route optimization and its applications in travelling salesman problem

An improved ant colony optimization algorithm based on route...

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7th IEEE International Conference on Bioinformatics and Bioengineering, BIBE

作者： Zhang, Yi Pei, Zhi-Li Yang, Jin-Hui Liang, Yan-Chun College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Department of Computer Science Jilin Business and Technology College College of Mathematics and Computer Science Inner Mongolia University for Nationalities

ISBN: (纸本)1424415098

In this paper, we introduce two improvements on Ant Colony Optimization (ACO) algorithm: route optimization and individual variation. The first is an optimized implementation of ACO, by which the running time of ants routing is largely reduced. The results of the simulated experiments show that the improved algorithm not only reduces the number of routing in the ACO but also surpasses existing algorithms in performance in solving large-scale TSP problems. In the second improvement, we introduce individual variation to ACO, by which the ants have different routing strategies. Simulation results show that the speed of convergence of ACO algorithm could be enhanced greatly. ©2007 IEEE.

关键词： Ant colony optimization

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A Method of Gene-Function Annotation Based on Variable Precision Rough Sets

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Journal of Bionic Engineering 2007年第3期4卷 177-184页

作者： Zhi-li Pei Xiao-hu Shi Meng Niu Xu-ning Tang Li-sha Liu Ying Kong Yan-chun Liang College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Changchun 130012 P. R. China College of Mathematics and Computer Science Inner Mongolia University for NationalitiesTongliao 028043 P. R. China College of Software Jilin University Changchun 130012 P. R. China Department of Biochemistry and Molecular Biology Institution of Glycobiology Dalian Medical University Dalian 116027 P. R. China

It is very important in the field of bioinformatics to apply computer to perform the function annotation for new sequenced bio-sequences. Based on GO database and BLAST program, a novel method for the function annotation of new biological sequences is presented by using the variable-precision rough set theory. The proposed method is applied to the real data in GO database to examine its effectiveness. Numerical results show that the proposed method has better precision, recall-rate and harmonic mean value compared with existing methods.

关键词： gene function annotation variable precision rough set GO BLAST

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A populations evolution study using the genotype frequency data of single nucleotide polymorphism from Y-chromosome

A populations evolution study using the genotype frequency d...

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2007 1st International Conference on Bioinformatics and Biomedical Engineering, ICBBE

作者： Pei, Zhili Kong, Ying Shi, Xiaohu Lian, Zhichao Tang, Xuning Liu, Lisha Cao, Zhongbo Liang, Yanchun Key Laboratory of Symbol Computation and Knowledge Engineering Jilin University Ministry of Education Chang'chun 130012 China College of Mathematics and Computer Science Inner Mongolia University for Nationalities Tong'liao 028043 China Department of Biochemistry and Molecular Biology Institution of Glycobiology Dalian Medical University Da'lian 116027 China

ISBN: (纸本)1424411203

This paper proposes a novel way for the population evolution research. In the paper, it constructs the phylogenies tree of four populations using the single nucleotide polymorphism (SNP) genotype frequency of human's Y-chromosome provided by the international Hapmap project firstly, then a mathematical model is proposed to calculate the distance of any two races for all SNP genotype frequency. The simulation results suggest that the theory of constructing phylogenetic tree by analyzing SNP genotype frequency is effective. The accuracy of the adopted processing method is also shown by the simulation results. About the origination of modern human being, the result of this study can support the 'out of Africa' hypothesis, and this result is same as most evidences of paleontology. © 2007 IEEE.

关键词： Gene expression

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A New Seamless Multi-resolution Simplification Method for the Terrain Model

A New Seamless Multi-resolution Simplification Method for th...

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Web Intelligence and Intelligent Agent Technology Workshops (WI-IAT)

作者： Huijie Zhang Jigui Sun Changsong Qi Nan Lv College of Computer Northeast Normal University Changchun China College of Computer Science & Technology Jilin University Changchun China College of Computer Science & Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University China

This paper presents a fast method to construct the simplified terrain model with the multi-resolution. In this method, we adopt the normal quad-tree hierarchy to subdivide the original terrain surface into the multi- resolution levels. For the sake of implementing the compressive storage and the efficient index for the elevation data, a connotative hierarchy is proposed and its corresponding index strategies are deduced. On the basis of the connotative hierarchy, we focus on resolving the crack problem of the simplified model. We firstly create the space filling curve during the simplification process to accelerate the search for the potential cracks. Afterwards, the different approaches are utilized to process the cracks in terms of the dissimilar terrain features. For this reason, we put forward an evaluation function that can selfadaptively identify the terrain feature according to the normal vector angle of the adjacent nodes in the connotative hierarchy. Consequently, there are not redundant triangles in our seamless multi-resolution terrain model. The proposed approaches are experimented on the real data and the results show that our method is relatively efficient and robust. Besides, the seamless simplified model has less number of triangles than the other common algorithm.

关键词： Multiresolution analysis educational institutions Intelligent agent Computer science Surface cracks Filling Conferences Acceleration Robustness Sun

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Text Categorization Method Based on Improved Mutual Information and Characteristic Weights Evaluation Algorithms

Text Categorization Method Based on Improved Mutual Informat...

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International Conference on Fuzzy Systems and Knowledge Discovery (FSKD)

作者： Zhili Pei Xiaohu Shi Maurizio Marchese Yanchun Liang College of Computer Science and Technology Key Laboratory of Symbol Computation and Knowledge Engineering of the Ministry of Education Jilin University Changchun China College of Mathematics & Computer Science National University of Inner Mongolia Tongliao China Department of Information and Communication Technology University of Trento Povo TN USA

The improvement of text categorization by statistical methods can be performed from two main directions, namely the feature selection and the evaluation of characteristic weights. In this paper, we propose an enhanced text categorization method based on a modified mutual information algorithm and evaluation algorithm of characteristic weights which improves both aspects. The proposed method is applied to the benchmark test set Reuters-21578 Top10 to examine its effectiveness. Numerical results show that the precision, the recall and the value of F1 of the proposed method are all superior to those of existing conventional methods.

关键词： Text categorization Mutual information Frequency shift keying Frequency estimation Computer science Statistical analysis Testing educational institutions Communications technology Performance evaluation

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