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Hyponymy Graph Model for Word Semantic Similarity Measurement

Chinese Journal of Electronics 2015年第1期24卷 96-101页

作者： WANG Junhua ZUO Wanli PENG Tao College of Computer Science and Technology Jilin University Key Laboratory of Symbol Computation and Knowledge Engineering attached to the Ministry of Education

Measuring word semantic similarity is a generic problem with a broad range of applications such as ontology mapping, computational linguistics and artificial intelligence. Previous approaches to computing word semantic similarity did not consider concept occurrence frequency and word’s sense number. This paper introduced Hyponymy graph, and based on which proposed a novel word semantic similarity model. For two words to be compared, we first retrieve their related concepts; then produce lowest common ancestor matrix and distance matrix between concepts; finally calculate distance-based similarity and information-based similarity, which are integrated to get final semantic similarity. The main contribution of our method is that both concept occurrence frequency and word’s sense number are taken into account. This similarity measurement more closely fits with human rating and effectively simulates human thinking process. Our experimental results on benchmark dataset M&C and R&G with Word Net2.1 as platform demonstrate roughly 0.9%–1.2%improvements over existing best approaches.

关键词： Word semantic similarity Concept semantic similarity Semantic similarity Hyponymy graph model Word Net.

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Otsu multi-thresholding based on DCG3A for medical image

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ICIC Express Letters, Part B: Applications 2016年第8期7卷 1651-1656页

作者： Fang, Zheng Shen, Xuanjing Chen, Haipeng Feng, Yuncong College of Computer Science and Technology Jilin University No. 2699 Qianjin Ave. Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University No. 2699 Qianjin Ave. Changchun130012 China

In order to solve the problem that multi-thresholding segmentation spends too much time finding the optimal solution in medical image segmentation, Otsu multi-thresholding based on dynamic combination of genetic algorithm and ant algorithm (abbreviated as DCG3A-OM) was proposed in this paper. Firstly, the algorithm uses genetic algorithm to generate preliminary partition results, and then converts them into the initial information of ant colony. Finally ant algorithm will approach to optimal values efficiently. While running genetic algorithm, the conditions of combination will be analyzed dynamically to avoid stopping genetic algorithm early or late. Besides, it increases the probability of variation and decreases the numbers of individuals which are calculated for the evolution rate of colony. The experimental results demonstrate that DCG3A-OM gets the optimal solution more quickly and efficiently than the others, and it can always get the optimal values mostly. © 2016 ICIC International.

关键词： Genetic algorithms

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The BBC News Hunter: A Novel Crawler for BBC News

The BBC News Hunter: A Novel Crawler for BBC News

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The Second International Conference of Young Computer Scientists, Engineers and Educators,ICYCSEE 2016

作者： Mingxin Wang Ning Wang Boran Wang Can Tian Yanchun Liang Guozhong Zhao Xiaosong Han College of Software Jilin University Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry College of Computer Science and Technology Jilin University Zhuhai Laboratory of Key Laboratory for Symbol Computation and Knowledge Engineering of Ministry of Education Zhuhai College of Jilin University Daqing Oilfield Personnel Development Institute CNPC

In order to distinguish and extract the topic information from other interferential information on the BBC news website for the study in social computing, the BBC News Hunter was proposed in this paper. The whole system consists of 6 subsystems, respectively named: UI, Control, Download, Analysis,Storage and Log. Numerical experiments show that satisfactory results can be obtained from the BBC news website, whose average accuracy as well as efficiency are acceptable.

关键词： BBC Crawler News HTML parser Multithread

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Research on Trust Prediction from a Sociological Perspective

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Journal of Computer Science & Technology 2015年第4期30卷 843-858页

作者：王英王鑫左万利 College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun 130012 China School of Computer Technology and Engineering Changehun Institute of Technology Changchun 130012 China

Trust, as a major part of human interactions, plays an important role in helping users collect reliable infor-mation and make decisions. However, in reality, user-specified trust relations are often very sparse and follow a power law distribution; hence inferring unknown trust relations attracts increasing attention in recent years. Social theories are frameworks of empirical evidence used to study and interpret social phenomena from a sociological perspective, while social networks reflect the correlations of users in real world; hence, making the principle, rules, ideas and methods of social theories into the analysis of social networks brings new opportunities for trust prediction. In this paper, we investigate how to exploit homophily and social status in trust prediction by modeling social theories. We first give several methods to compute homophily coe？cient and status coe？cient, then provide a principled way to model trust prediction mathe-matically, and propose a novel framework, hsTrust, which incorporates homophily theory and status theory. Experimental results on real-world datasets demonstrate the effectiveness of the proposed framework. Further experiments are conducted to understand the importance of homophily theory and status theory in trust prediction.

关键词： trust prediction homophily coefficient status coefficient social theory matrix factorization

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A Chinese Topic Crawler Focused on Customer Development

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Procedia CIRP 2016年 56卷 476-480页

作者： Tong Wu Yanchun Liang Chunguo Wu Shifeng Piao Deyin Ma Guozhong Zhao Xiaosong Han College of Computer Science and Technology Key Laboratory for Symbol Computation and Knowledge Engineering of National Education Ministry Jilin University Changchun 130012 China Zhuhai Laboratory of Key Laboratory for Symbol Computation and Knowledge Engineering of Ministry of Education Zhuhai College of Jilin University Zhuhai 519041 China School of Business Jilin University Changchun 130012 China Daqing Oilfield Personnel Development Institute CNPC Daqing 163000 China

This paper presents a Chinese topic crawler focused on customer development, in order to meet the needs of users for more accurate and particular Internet information. The concept of meta-search engine is introduced, and the keywords are expanded by the ontology of HowNet. Through the web crawler, preprocessing and classification, the information on customer relations can be divided into three categories: company, platform and meaningless. Numerical experiments show that satisfactory results can be obtained in some particular information-seeking areas. The average accuracy for classification is more than 80%, which can meet customer needs in most cases.

关键词： Topic crawler Customer development Meta-search engine Semantic similarity

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A Sustainable City Planning Algorithm Based on TLBO and Local Search

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IOP Conference Series: Materials Science and engineering 2017年第1期242卷

作者： Ke Zhang Li Lin Xuanxuan Huang Yiming Liu Yonggang Zhang College of Computer Science and Technology Jilin University Changchun 130012 China Key Laboratory of Symbol Computation and Knowledge Engineering (Jilin University) Ministry of Education Changchun 130012 China

Nowadays, how to design a city with more sustainable features has become a center problem in the field of social development, meanwhile it has provided a broad stage for the application of artificial intelligence theories and methods. Because the design of sustainable city is essentially a constraint optimization problem, the swarm intelligence algorithm of extensive research has become a natural candidate for solving the problem. TLBO (Teaching-Learning-Based Optimization) algorithm is a new swarm intelligence algorithm. Its inspiration comes from the 'teaching' and 'learning' behavior of teaching class in the life. The evolution of the population is realized by simulating the 'teaching' of the teacher and the student 'learning' from each other, with features of less parameters, efficient, simple thinking, easy to achieve and so on. It has been successfully applied to scheduling, planning, configuration and other fields, which achieved a good effect and has been paid more and more attention by artificial intelligence researchers. Based on the classical TLBO algorithm, we propose a TLBO_LS algorithm combined with local search. We design and implement the random generation algorithm and evaluation model of urban planning problem. The experiments on the small and medium-sized random generation problem showed that our proposed algorithm has obvious advantages over DE algorithm and classical TLBO algorithm in terms of convergence speed and solution quality.

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The Improved Characteristics of Bionic Gabor Representations by Combining with SIFT key-points for Iris Recognition

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Journal of Bionic engineering 2015年第3期12卷 504-517页

作者： Yuanning Liu Fei He Xiaodong Zhu Zhen Liu Ying Chen Ye Han Lijiao Yu 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 Chanschun 130012 China Graduate School of Engineering Nagasaki Institute of Applied Science Japan College of Software Nanchang Hangkong University Nanchang 330063 China

Gabor filters are generally regarded as the most bionic filters corresponding to the visual perception of human. Their filtered coefficients thus are widely utilized to represent the texture information of irises. However, these wavelet-based iris representations are inevitably being misaligned in iris matching stage. In this paper, we try to improve the characteristics of bionic Gabor representations of each iris via combining the local Gabor features and the key-point descriptors of Scale Invariant Feature Transformation （SIFT）, which respectively simulate the process of visual object class recognition in frequency and spatial domains. A localized approach of Gabor features is used to avoid the blocking effect in the process of image division, meanwhile a SIFT key point selection strategy is provided to remove the noises and probable misaligned key points. For the combination of these iris features, we propose a support vector regression based fusion rule, which may fuse their matching scores to a scalar score to make classification decision. The experiments on three public and self-developed iris datasets validate the discriminative ability of our multiple bionic iris features, and also demonstrate that the fusion system outperforms some state-of-the-art methods.

关键词： iris recognition bionic Gabor features scale invariant feature transformation support vector regression score level fusion

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Attribute selection for job shop scheduling problem based on concept lattice

Attribute selection for job shop scheduling problem based on...

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第27届中国过程控制会议（CPCC2016）

作者： Wang Zhenjiang Cao Zhengcai Liu Minjilin College of Information Science and Technology Beijing University of Chemical Technology Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education University Department of Automation Tsinghua University

Attribute selection is an effective approach to improve the inference efficiency of data-based schedulingstrategies system and many researchers have studied the attribute selection based on computational intelligence *** computational intelligence methods,concept lattice,an important tool for knowledge extraction andanalysis,has nature advantages in attribute

关键词： Attribute selection for job shop scheduling problem based on concept lattice

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Heterogeneous data mining for planning active surveillance of malaria 15

Heterogeneous data mining for planning active surveillance o...

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ASE BigData and SocialInformatics, ASE BD and SI 2015

作者： Gu, Xiao Chen, Hechang Yang, Bo College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education China

ISBN: (纸本)9781450337359

Malaria is one of the most serious diseases in the world, which is densely distributed in poverty and remote areas. In the prevention and control of malaria, active surveillance is more efficient than passive surveillance to discover the incidences timely and accurately. However, it is always faced with the challenge of how to allocate the limited sources, such as medical staff and medicine, appropriately so as to achieve a maximum infect. In this paper, we propose a novel method to characterize the spatiotemporal patterns of infection risk for active surveillance planning. Specifically, we propose a temporal heterogeneous diffusion network model to discover high risk areas timely, and a mixture optimization method to find high risk areas accurately. The validation on existing real-world data shows that our method outperforms the existing state-of-the-art both in terms of infection risk prediction and planning of active surveillance under different thresholds. © 2015 ACM.

关键词： Mixtures

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A bio-inspired method for locating the diffusion source with limited observers

A bio-inspired method for locating the diffusion source with...

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Congress on Evolutionary computation

作者： Yuxin Liu Chao Gao Xinyan She Zili Zhang College of Computer and Information Science & College of Software Southwest University Chongqing China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Jilin University Changchun China School of Information Technology Deakin University Geelong VIC Australia

ISBN: (纸本)9781509006243

Locating the source of diffusion is a challenging problem in complex networks and has great practical significance for restraining rumors propagation and controlling epidemics spreading. An efficient locating method should have a higher locating accuracy with the minimum required information. Although existing locating methods based on observers consider the time delays of edges, they compute the time delays based on the shortest path, which may differ from the actual diffusion process. Moreover, the higher locating accuracy of traditional method with observers has a great dependence on the assumption that the propagation delays along edges follow a definite distribution such as the Gaussian distribution. In order to solve these shortcomings, this paper proposes a Physarum-inspired method to locate the diffusion source that is independence of the distribution of propagation delays. Our method quantifies the nutrient transportation process in the adaptive network evolved by Physarum, which is used to simulate the information or epidemic diffusion routes in a social network. Simulation results on various benchmark networks show that our method has a better performance in terms of error distance than that of Gaussian method without assuming the definite distribution of time delays. Together with the advantage that our method does not require the sender information of observers compared with existing methods, our method allows for a wider range of applications in the real-world networks.

关键词： Electron tubes Observers Diffusion processes Adaptive systems Propagation delay Conductivity

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