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26th International Conference on computational Linguistics, COLING 2016

作者： Li, Ximing Chi, Jinjin Li, Changchun Ouyang, Jihong Fu, Bo College of Computer Science and Technology Jilin University China Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education China College of Computer and Information Technology Liaoning Normal University China

ISBN: (纸本)9784879747020

Gaussian LDA integrates topic modeling with word embeddings by replacing discrete topic distribution over word types with multivariate Gaussian distribution on the embedding space. This can take semantic information of words into account. However, the Euclidean similarity used in Gaussian topics is not an optimal semantic measure for word embeddings. Acknowledgedly, the cosine similarity better describes the semantic relatedness between word embeddings. To employ the cosine measure and capture complex topic structure, we use von Mises-Fisher (vMF) mixture models to represent topics, and then develop a novel mix-vMF topic model (MvTM). Using public pre-trained word embeddings, we evaluate MvTM on three real-world data sets. Experimental results show that our model can discover more coherent topics than the state-of-the-art baseline models, and achieve competitive classification performance. © 1963-2018 ACL.

关键词： Embeddings

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Group sparse Bayesian learning for active surveillance on epidemic dynamics

arXiv

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arXiv 2017年

作者： Pei, Hongbin Yang, Bo Liu, Jiming Dong, Lei College of Computer Science and Technology Jilin University Changchun China Key Laboratory of Symbolic Computation Knowledge Engineering of Ministry of Education China Department of Computer Science Hong Kong Baptist University Hong Kong Institute of Remote Sensing and Geographical Information Systems Peking University Beijing China

Predicting epidemic dynamics is of great value in understanding and controlling diffusion processes, such as infectious disease spread and information propagation. This task is intractable, especially when surveillance resources are very limited. To address the challenge, we study the problem of active surveillance, i.e., how to identify a small portion of system components as sentinels to effect monitoring, such that the epidemic dynamics of an entire system can be readily predicted from the partial data collected by such sentinels. We propose a novel measure, the γ value, to identify the sentinels by modeling a sentinel network with row sparsity structure. We design a flexible group sparse Bayesian learning algorithm to mine the sentinel network suitable for handling both linear and non-linear dynamical systems by using the expectation maximization method and variational approximation. The efficacy of the proposed algorithm is theoretically analyzed and empirically validated using both synthetic and real-world data. Copyright © 2017, The Authors. All rights reserved.

关键词： Monitoring

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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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A local gradient based peak search algorithm for three-dimensional rotation electron diffraction image processing

A local gradient based peak search algorithm for three-dimen...

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International Conference on Systems and Informatics (ICSAI)

作者： Xinzheng Dong Yixuan Wang He Yin Zhuhai College of Jilin University Zhuhai Laboratory of Key Laboratory of Symbolic Computation and Knowledge Engineering of Ministry of Education Zhuhai China

ISBN: (纸本)9781509055227

Peak search for three-dimensional rotation electron diffraction image is almost the most important step in crystal structure determination. The difference of Gaussian method is the traditional approach for this task with the disadvantage that values of three tunable parameters need to be determined by users. To address this drawback, this paper presents a local gradient based peak search algorithm that needs only one tunable parameter. Experiments show that our proposed method is as effective as the difference of Gaussian method in peak detection task, but has obvious advantages in speed and convenience.

关键词： Diffraction Dogs Kernel Standards Software algorithms Shape

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Biogeography-based optimization for cluster analysis

Biogeography-based optimization for cluster analysis

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International Conference on Computer, Communication and computational Sciences, ICCCCS 2016

作者： Wu, Xueyan Wang, Hainan Chen, Zhimin Lu, Zhihai Phillips, Preetha Wang, Shuihua Zhang, Yudong School of Computer Science and Technology Nanjing Normal University NanjingJiangsu210023 China Key Laboratory of Statistical Information Technology & Data Mining State Statistics Bureau ChengduSichuan610225 China School of Computer and Information Engineering Henan Normal University XinxiangHenan453000 China School of Electronic Information Shanghai Dianji University Shanghai200240 China Key Laboratory of Symbolic Computation & Knowledge Engineering of Ministry of Education Jilin University ChangchunJilin130012 China Guangxi Key Laboratory of Manufacturing System & Advanced Manufacturing Technology GuilinGuangxi541004 China School of Natural Sciences and Mathematics Shepherd University ShepherdstownWV25443 United States West Virginia School of Osteopathic Medicine 400 N Lee St LewisburgWV24901 United States Department of Electrical Engineering The City College of New York CUNY New YorkNY10031 United States State Key Lab of CAD & CG Zhejiang University HangzhouZhejiang310027 China Manchester Metropolitan University ManchesterM156BH United Kingdom

ISBN: (纸本)9789811037696

With the aim of resolving the issue of cluster analysis more precisely and validly, a new approach was proposed based on biogeography-based optimization (abbreviated as BBO) algorithm. (Method) First, we reformulated the problem with an optimization model based on the variance ratio criterion (VARAC). Then, BBO was presented to search the optimal solution of the VARAC. There are 400 data of four groups in the experimental dataset, which have the degrees of overlapping of three distinct scales. The first one is nonoverlapping, the second one is partial overlapping, and the last is severely overlapping. BBO algorithm was compared with three different state-of-the-art approaches. We ran every algorithm 20 times. In this experiment, our results demonstrate the maximum VARAC values that can be found by BBO. The conclusion is that BBO is predominant which is extremely quick for the issue of clustering analysis. © Springer Nature Singapore Pte Ltd. 2017.

关键词： Cluster analysis

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Integrity Constraint Validation in DL-LiteR Based Ontology Using Rewriting

Integrity Constraint Validation in DL-LiteR Based Ontology U...

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

作者： Xianji Cui Dantong Ouyang Jialiang He College of Information and Communication Engineering Dalian Minzu University Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Jilin University

With the rapid development of information technology,semantic web data present features of massiveness and complexity. As the data-centric science, social computing have great influence in collecting and analyzing semantic data. In our contribution, we propose an integrity constraint validation for DL-Lite R based ontology in view of data correctness issue in the progress of social computing ***, at the basis of translations from integrity constraint axioms into a set of conjunctive queries, integrity constraint validation is converted into the conjunctive query answering over knowledge bases. Moreover, rewriting rules are used for reformulating the integrity constraint axioms using standard axioms. On this account, the integrity constraint validation can be reduced to the query evaluation over the ABox, and use query mechanisms in database management systems to optimize integrity constraint validation. Finally, the experimental result shows that the rewritingbased method greatly improves the efficiency of integrity constraint validation and is more appropriate to scalable data in the semantic web.

关键词： Semantic web Social computing Integrity constraints Conjunctive query Rewriting

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The Fitzpatrick-Neville-Type Algorithm for Multivariate Vector-Valued Osculatory Rational Interpolation

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Journal of Systems Science & Complexity 2015年第1期28卷 222-242页

作者： XIA Peng ZHANG Shugong LEI Na KIM Zhangyong School of Mathematics Liaoning University Automated Reasoning and Cognition Key Laboratory of Chongqing School of Mathematics Key Laboratory of Symbolic Computation and Knowledge Engineering(Ministry of Education)Jilin University

In this paper,the authors first apply the Fitzpatrick algorithm to multivariate vectorvalued osculatory rational *** based on the Fitzpatrick algorithm and the properties of an Hermite interpolation basis,the authors present a Fitzpatrick-Neville-type algorithm for multivariate vector-valued osculatory rational *** may be used to compute the values of multivariate vector-valued osculatory rational interpolants at some points directly without computing the interpolation function explicitly.

关键词： Fitzpatrick algorithm GrSbner basis module vector-valued osculatory rational interpolation.

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A concurrent model for temporal hierarchical task network

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Journal of computational and Theoretical Nanoscience 2016年第5期13卷 3135-3138页

作者： Feng, Yuxuan Ouyang, Dantong Feng, Shasha Liu, Jie College of Computer Science and Technology Jilin University Changchun130012 China Key Laboratory of Symbolic Computation and Knowledge Engineering Ministry of Education Changchun130012 China

When several actions preformed at the same time, or performed concurrently, the possibility of multiple concurrent and mutually interacting make the planning solving process difficult. In this paper, we reform the framework of hierarchical task network planning paradigm to present the concurrent action planning, to make good use of domain knowledge to improve the performance of planner. There are several remarkable works deal with temporal planning problem by hierarchical task network planning paradigm, our work focus on the concurrent performing actions. The experimental results is positive. Copyright © 2016 American Scientific Publishers All rights reserved.

关键词： Nanoscience

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Classification of evaluation measurement taken predicted scores into account

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Journal of Information and computational Science 2015年第5期12卷 1723-1730页

作者： Ding, Tienan Li, Xiongfei Key Laboratory of Symbol Computation and Knowledge Engineer of Ministry of Education Jilin University Changchun China College of Computer Science and Technology Jilin University Changchun China

Classifying performance evaluation is one of open problems in data mining and machine learning fields. We note that nearly all the existing evaluation measures ignore the predicted probabilities which are greatly significant in the process of classifiers' evaluation. In this paper, we construct a weighted confusion matrix to reflect the information on predicted probabilities. In addition, based on the weighted confusion matrix, traditional evaluation measures, such as accuracy, precision, recall, F-measure, are redefined to taking predicted probabilities into account. Finally, properties of the re-written evaluation measures are investigated. Experimental results show that the re-defined evaluation measures are superior to traditional ones in terms of discrimination. Copyright © 2015 Binary Information Press.

关键词： Probability

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