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Clonal Selection Based Memetic Algorithm for Job Shop Scheduling Problems

Journal of Bionic engineering 2008年第2期5卷 111-119页

作者： Jin-hui Yang Liang Sun Heow Pueh Lee Yun Qian Yan-chun Liang College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering of Ministry of Education Changchun 130012 P. R. China Institute of High Performance Computing Singapore 117528 Singapore Department of Mechanical Engineering National University of Singapore Singapore 117576 Singapore Institute of Electric and Information Engineering Beihua University Jilin 13202 l P. R. China

A clonal selection based memetic algorithm is proposed for solving job shop scheduling problems in this paper. In the proposed algorithm, the clonal selection and the local search mechanism are designed to enhance exploration and exploitation. In the clonal selection mechanism, clonal selection, hypermutation and receptor edit theories are presented to construct an evolutionary searching mechanism which is used for exploration. In the local search mechanism, a simulated annealing local search algorithm based on Nowicki and Smutnicki＇s neighborhood is presented to exploit local optima. The proposed algorithm is examined using some well-known benchmark problems. Numerical results validate the effectiveness of the proposed algorithm.

关键词： job shop scheduling problem clonal selection algorithm simulated annealing global search local search

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Translating query for deep web using ontology

Translating query for deep web using ontology

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International Conference on Computer Science and Software engineering, CSSE 2008

作者： Hao, Hang Wanli, Zuo Fei, Ren Junhua, Wang College of Computer Science and Technology Jilin University Department of Information Science and Technology Changchun Taxation College Changchun 130117 China Key Laboratory of Symbol Computation and Knowledge Engineering Ministry of Education Changchun 130012 China College of Computer Science and Technology Jilin University Changchun 130012 China

ISBN: (纸本)9780769533360

The E-commerce information on the Surface Web is supported by the Deep Web, which can not be accessed directly by the search engines or the web crawlers. The only way to access the backend database is through query interface. Extracting valid attributes from the query forms and automatic translating the source query into a target query is a solvable way for addressing the current limitations in accessing Deep Web data sources. To generate a valid query, we have to reconcile the key attributes and their semantic relation. We present our framework to solve the problem. To enrich the set of attributes contained in the semantic form, we use the WordNet as kinds of ontology technique and we try to find the semantic relation of the attributes in the same query from and different forms. Extensive experiments over real-word domains show the utility of our query translation framework. © 2008 IEEE.

关键词： Ontology

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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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Translating Query for Deep Web Using Ontology

Translating Query for Deep Web Using Ontology

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International Conference on Computer Science and Software engineering

作者： Hao Liang Wanli Zuo Fei Ren Junhua Wang College of Computer Science and Technology Department of Technology Jilin University Changchun Taxation China College of Computer Science and Technology Key Laboratory of Symbol Computation andKnowledge Engineering of the Ministry of Education Jilin University China College of Computer Science and Technology Jilin University Changchun China College of Computer Science and Technology Jilin University Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Changchun China

ISBN: (纸本)9781424439027

The e-commerce information on the surface Web is supported by the Deep Web, which can not be accessed directly by the search engines or the Web crawlers. The only way to access the backend database is through query interface. Extracting valid attributes from the query forms and automatic translating the source query into a target query is a solvable way for addressing the current limitations in accessing Deep Web data sources. To generate a valid query, we have to reconcile the key attributes and their semantic relation. We present our framework to solve the problem. To enrich the set of attributes contained in the semantic form, we use the WordNet as kinds of ontology technique and we try to find the semantic relation of the attributes in the same query from and different forms. Extensive experiments over real-word domains show the utility of our query translation framework.

关键词： Ontologies Databases Computer science educational institutions Search engines Data mining Laboratories knowledge engineering Computer science education Crawlers

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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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Prewavelets with finite decomposition and finite reconstruction

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Journal of Information and computational Science 2007年第1期4卷 35-41页

作者： Guan, Yujing Li, Ying Jiang, Zhengyi Institute of Mathematics Jilin University Changchun 130021 China State Key Laboratory of Intelligent Technology and Systems Department of Computer Science and Technology Tsinghua University Beijing 100084 China College of Computer Science and Technology Jilin University Changchun 130021 China Key Laboratory of Symbol Computation and Knowledge Engineering Changchun 130021 China

The necessary and sufficient condition for the existence of prewavelets with finite decomposition and finite reconstruction is presented. Especially when r = 1, we show that {φj(x-k) | 1 &le j &le r, k ∈ s} is shift-orthogonal if there exist prewavelets with finite decomposition and finite reconstruction, i.e., non-trivial prewavelets with finite decomposition and finite reconstruction does not exist. As an example, when r = 2 we construct a prewavelet with finite decomposition and finite reconstruction where the scale function is not shift-orthogonal, which demonstrate that there exist vector prewavelets with finite decomposition and finite reconstruction.

关键词： Wavelet transforms

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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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An ontology-based method in information translation

An ontology-based method in information translation

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2nd International Conference on Semantics, knowledge, and Grid, SKG 2006

作者： Bai, Yan Liu, Dayou Open Symbol Computation and Knowledge Engineering Laboratory of State Education Ministry College of Computer Science and Technology Jilin University China

ISBN: (纸本)076952673X

An ontology-based method named AOBM is proposed in this paper. It fully takes into account the factors that will afect the communication, and using ontology can be represented in agent's knowledge base. Pmvided ontology did not belong to the public data or have any public ontology, AOBM establishes a layering algorithm, which is able to avoid logical exception handling policies, ensure the right understanding of the communication entity concept, and resolve the consistency problem of the concept translation. Experimental results show that AOBM is superior to other methods, and can effectively improve the communication consistency of a mobile agent system under certain conditions. © 2006 IEEE.

关键词： Ontology

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