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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8787卷 141-157页

作者： Zhu, Feng Liu, Guanfeng Liu, An Zhao, Lei Zhou, Xiaofang School of Computer Science and Technology Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University Suzhou215006 China School of Information Technology and Electrical Engineering University of Queensland Brisbane4072 Australia

Online Social Networks (OSNs) are becoming popular and attracting lots of participants. In OSN based e-commerce platforms, a buyer’s review of a product is one of the most important factors for other buyers’ decision makings. A buyer who provides high quality reviews thus has strong social influence, and can impact a large number of participants’ purchase behaviours in OSNs. However, the dishonest participants can cheat the existing social influence evaluation models by using some typical attacks, like Constant and Camouflage, to obtain fake strong social influence. Therefore, it is significant to accurately evaluate such social influence to recommend the participants who have strong social influences and provide high quality product reviews. In this paper, we propose an Evolutionary-Based Robust Social Influence (EB-RSI) method based on the trust evolutionary models. In our EB-RSI, we propose four influence impact factors in social influence evaluation, i.e., Total Trustworthiness (TT), Fluctuant Trend of Being Advisor (FTBA), Fluctuant Trend of Trustworthiness (FTT) and Trustworthiness Area (TA). They are all significant in the influence evaluation. We conduct experiments onto a real social network dataset Epinions, and validate the effectiveness and robustness of our EB-RSI by comparing with state-of-the-art method, SoCap. The experimental results demonstrate that our EB-RSI can more accurately evaluate participants’ social influence than SoCap. © Springer International Publishing Switzerland 2014.

关键词： Social networking (online)

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MicroBlog orientation analysis based on sentiment symbol

MicroBlog orientation analysis based on sentiment symbol

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2014 International Conference on Manufacturing technology and Electronics Applications, ICMTEA 2014

作者： Liu, Pei Yu Zhang, Yan Hui Wei, Jing Xun Hou, Xiu Yan School of Information Engineering Shandong Yingcai University Jinan China Department of Information Science and Engineering Shandong Normal University China Shandong Provincial Key Laboratory for Distributed Computer Software Novel Technology China

ISBN: (纸本)9783038353287

As a new social networking media, Micro-blog is recognized by more and more people gradually, the orientation analysis of Micro-blog short text messages has become a hotspot in the field of data mining. At present, the research of Micro-blog orientation analysis mainly concentrate in the text, without considering the impact of other emotional factors. By analyzing and studying Sina Micro-blog, this paper added new words and emoticons in the basis of traditional emotional dictionary to construct special Micro-blog dictionary. Meanwhile, it analyzed rhetoric and sentence to improve the effect of orientation analysis. The experimental results showed that the method in Micro-blog orientation analysis obtained better performance. © (2014) Trans Tech Publications, Switzerland.

关键词： Data mining

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Model Checking Parallel Interval Logic on Parallel Run Structures

Model Checking Parallel Interval Logic on Parallel Run Struc...

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2012 Third International Conference on Theoretical and Mathematical Foundations of computer Science(ICTMF 2012)

作者： Zining Cao Department of Computer Science and Technology Nanjing University of Aero.& Astro. Provincial Key Laboratory for Computer Information Processing Technology Soochow University

In this paper,we firstly present a kind of models for truly concurrent systems named parallel run *** we present a parallel interval logic,called PIL,which is an extension of interval ***,we give an algorithm of model... 详细信息

关键词： Model Checking,Truly Concurrent Systems,Temporal Logic

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A Complete Proof System of Weak Bisimulation Over a Linear HOcore

A Complete Proof System of Weak Bisimulation Over a Linear H...

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2012 Third International Conference on Theoretical and Mathematical Foundations of computer Science(ICTMF 2012)

作者： Zining Cao Department of Computer Science and Technology Nanjing University of Aero.& Astro. Provincial Key Laboratory for Computer Information Processing Technology Soochow University

In this short paper,we show the equivalence between weak context bisimulation and strong bisimulation for the linear *** as a corollary,we get a complete proof system of weak context bisimulation over the linear HOcore.

关键词： Process Calculi,Bisimulation,Proof System,Higher Order pi Calculus

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Experimental Verification of a Multi-robot Distributed Control Algorithm with Containment and Group Dispersion Behaviors: the Case of Dynamic Leaders

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IEEE/CAA Journal of Automatica Sinica 2014年第1期1卷 54-60页

作者： Hejin Zhang Zhiyun Zhao Ziyang Meng Zongli Lin Department of Automation and Key Laboratory for System Control and Information Processing of Ministry of Education Shanghai Jiao Tong University the Access Linnaeus Centre School of Electrical Engineering Royal Institute of Technology Charles L. Brown Department of Electrical and Computer Engineering University of Virginia

This paper studies the containment and group dispersion control for a multi-robot system in the presence of dynamic leaders. Each robot is represented by a doubleintegrator dynamic model and a distributed control algorithm is developed to drive the multi-robot system to follow a group of dynamic leaders with containment and group dispersion behaviors. The effectiveness of the algorithm is then verified on a multi-robot control platform.

关键词： Heuristic algorithms Mobile robots Robot kinematics Trajectory Dispersion Decentralized control

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Topic identification strategy for English academic resources

Topic identification strategy for English academic resources

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5th FTRA International Conference on computer Science and its Applications, CSA 2013

作者： Li, Huang Qing, Hu Xin, Xiong Lijun, Hua College of Computer Science and Technology Wuhan University of Science and Technology Wuhan 430080 China Hubei Province Key Laboratory of Intelligent Information Processing and Real-time Industrial System Wuhan 430080 China

ISBN: (纸本)9783642416736

The network resource grows up exponentially with the rapid development of Internet. It is very important to identify whether the resources belong to the professional field or not. However, resources in professional field are sorted up mostly manually at present, and some drawbacks exist in the process. To tackle with these problems, the Topic Identification Strategy of Academic Resources proposes topic identification method based on the main text of resources. The strategy first transfers different forms of academic resources into a unified format. And then break up the whole text into parts to calculate the topic degree of relevance. Samples are used to decide the weight of the thresholds. The proposed method could also add labels for resources automatically. Experiments show that, this strategy could effectively deal with English academic resources topic identification. © 2014 Springer-Verlag Berlin Heidelberg.

关键词： Data mining

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Automated localization and accurate segmentation of optic disc based on intensity within a minimum enclosing circle 8

Automated localization and accurate segmentation of optic di...

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8th IFIP International Conference on Intelligent information processing, IIP 2014

作者： Jiang, Ping Dou, Quansheng School of Computer Science and Technology Shandong Institute of Business and Technology Laishan Yantai264005 China Key Laboratory of Intelligent Information Processing in Universities of Shandong Shandong Institute of Business and Technology Laishan Yantai264005 China

ISBN: (纸本)9783662449790

This paper presents a method for automated localization and accurate segmentation of the optic disc. An intensity threshold is determined and select all the pixels whose intensities are greater than the threshold, by erosion the optic disc can be localized. By dilation and region filling, a minimum enclosing circle which can completely hold the optic disc is determined, within the circle, the vessels are eliminated by replacing the darker vessel pixels with brighter pixels. Define the intensity features of the optic disc boundary , and select the pixels according to the features, then the optic disc may be segmented. The experiment shows that compared to the active contour models, this method is more efficient and accurate on the boundary extraction of the optic disc. © IFIP International Federation for information processing 2014.

关键词： Pixels

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A heterogeneous graph model for social opinion detection 13

A heterogeneous graph model for social opinion detection

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13th International Conference on Machine Learning and Cybernetics, ICMLC 2014

作者： Liao, Xiangwen Huang, Yichao Wei, Jingjing Yu, Zhiyong Chen, Guolong College of Mathematics and Computer Science Fuzhou University Fuzhou350116 China College of Physics and Information Engineering Fuzhou University Fuzhou350116 China Fujian Provincial Key Laboratory of Network Computing and Intelligent Information Processing Fuzhou University Fuzhou350116 China

ISBN: (纸本)9783662456514

Microblogging services, such as Twitter, have become popular for people to share their opinions towards a broad range of topics. It is a great challenge to get an overview of some important topics by reading all tweets every day. Previous researches such as opinion detection and opinion summarization have been studied for this problem. However, these works mainly focus on the content of text without taking the quality of short text and features of social media into consideration. In this paper, we propose a heterogeneous graph model for users’ opinion detection on microblog. We first extract keywords of topics. Then, a three-level microblog graph is constructed by combining user influence, word importance, post significance, and topic periodicity. Microblog posts are ranked from different topics by using the random walk algorithm. Experimental results on real a dataset validate the effectiveness of our approach. In comparison with baseline approaches, the proposed method achieves 8% improvement. © Springer-Verlag Berlin Heidelberg 2014.

关键词： Random processes

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Ranking based activity trajectory search

Lecture Notes in Computer Science (including subseries Lectu...

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Lecture Notes in computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) 2014年 8786卷 170-185页

作者： Chen, Wei Zhao, Lei Jiajie, Xu Zheng, Kai Zhou, Xiaofang School of Computer Science and Technology Soochow University China Jiangsu Provincial Key Laboratory for Computer Information Processing Technology Soochow University China School of ITEE The University of Queensland Brisbane Australia

With the proliferation of the GPS-enabled devices and mobile techniques, there has been a lot of work on trajectory search in the last decade. Previous trajectory search has focused on spatio-temporal features and text descriptions. Different from them, we study a novel problem of searching trajectories with activities and corresponding ranking information. Given a query q, which is attached with a set of activities and a threshold of distance, the results of ranking based activity trajectory search (RTS) are k trajectories such that the given activities are performed with the highest ranking within the threshold of distance. In addition, we also extend the query with an order, i.e., order-sensitive ranking based activity trajectory search (ORTS), which takes both the order of activities in a query q and the order of trajectories into account. It is challenging to answer RTS and ORTS efficiently due to the structural complexity of trajectory data with ranking information. In this paper, a hybrid index AC-tree and its optimized variant RAC-tree are proposed to achieve higher efficiency. Extensive experiments verify the high efficiency and scalability of the proposed algorithms. © Springer International Publishing Switzerland 2014.

关键词： Trajectories

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Genetic analysis of over 1 million people identifies 535 new loci associated with blood pressure traits (vol 50, pg 1412, 2018)

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NATURE GENETICS 2018年第12期50卷 1755-1755页

作者： Evangelou, Evangelos Warren, Helen R. Mosen-Ansorena, David Mifsud, Borbala Pazoki, Raha Gao, He Ntritsos, Georgios Dimou, Niki Cabrera, Claudia P. Karaman, Ibrahim Fu Liang Ng Evangelou, Marina Witkowska, Katarzyna Tzanis, Evan Hellwege, Jacklyn N. Giri, Ayush Edwards, Digna R. Velez Sun, Yan V. Cho, Kelly Gaziano, J. Michael Wilson, Peter W. F. Tsao, Philip S. Kovesdy, Csaba P. Esko, Tonu Magi, Reedik Milani, Lili Almgren, Peter Boutin, Thibaud Debette, Stephanie Ding, Jun Giulianini, Franco Holliday, Elizabeth G. Jackson, Anne U. Li-Gao, Ruifang Lin, Wei-Yu Luan, Jian'an Mangino, Massimo Oldmeadow, Christopher Prins, Bram Peter Qian, Yong Sargurupremraj, Muralidharan Shah, Nabi Surendran, Praveen Theriault, Sebastien Verweij, Niek Willems, Sara M. Zhao, Jing-Hua Amouyel, Philippe Connell, John de Mutsert, Renee Doney, Alex S. F. Farrall, Martin Menni, Cristina Morris, Andrew D. Noordam, Raymond Pare, Guillaume Poulter, Neil R. Shields, Denis C. Stanton, Alice Thom, Simon Abecasis, Goncalo Amin, Najaf Arking, Dan E. Ayers, Kristin L. Barbieri, Caterina M. Batini, Chiara Bis, Joshua C. Blake, Tineka Bochud, Murielle Boehnke, Michael Boerwinkle, Eric Boomsma, Dorret I. Bottinger, Erwin P. Braund, Peter S. Brumat, Marco Campbell, Archie Campbell, Harry Chakravarti, Aravinda Chambers, John C. Chauhan, Ganesh Ciullo, Marina Cocca, Massimiliano Collins, Francis Cordell, Heather J. Davies, Gail de Borst, Martin H. de Geus, Eco J. Deary, Ian J. Deelen, Joris Del Greco, Fabiola M. Demirkale, Cumhur Yusuf Dorr, Marcus Ehret, Georg B. Elosua, Roberto Enroth, Stefan Erzurumluoglu, A. Mesut Ferreira, Teresa Franberg, Mattias Franco, Oscar H. Gandin, Ilaria Gasparini, Paolo Giedraitis, Vilmantas Gieger, Christian Girotto, Giorgia Goel, Anuj Gow, Alan J. Gudnason, Vilmundur Guo, Xiuqing Gyllensten, Ulf Hamsten, Anders Harris, Tamara B. Harris, Sarah E. Hartman, Catharina A. Havulinna, Aki S. Hicks, Andrew A. Hofer, Edith Hofman, Albert Hottenga, Jouke-Jan Huffman, Jennifer E. Hwang, Shih-Jen Ingelsson, Erik James, Alan Jansen Department of Epidemiology and Biostatistics Imperial College London London UK Department of Hygiene and Epidemiology University of Ioannina Medical School Ioannina Greece William Harvey Research Institute Barts and The London School of Medicine and Dentistry Queen Mary University of London London UK National Institute for Health Research Barts Cardiovascular Biomedical Research Center Queen Mary University of London London UK MRC-PHE Centre for Environment and Health Imperial College London London UK Department of Mathematics Imperial College London London UK Division of Epidemiology Department of Medicine Institute for Medicine and Public Health Vanderbilt Genetics Institute Vanderbilt University Medical Center Tennessee Valley Healthcare System (626)/Vanderbilt University Nashville TN USA Vanderbilt Genetics Institute Vanderbilt Epidemiology Center Department of Obstetrics and Gynecology Vanderbilt University Medical Center Tennessee Valley Health Systems VA Nashville TN USA Department of Epidemiology Emory University Rollins School of Public Health Atlanta GA USA Department of Biomedical Informatics Emory University School of Medicine Atlanta GA USA Massachusetts Veterans Epidemiology Research and Information Center (MAVERIC) VA Boston Healthcare System Boston MA USA Division of Aging Department of Medicine Brigham and Women’s Hospital Department of Medicine Harvard Medical School Boston MA USA Atlanta VAMC and Emory Clinical Cardiovascular Research Institute Atlanta GA USA VA Palo Alto Health Care System Division of Cardiovascular Medicine Stanford University School of Medicine Stanford CA USA Nephrology Section Memphis VA Medical Center and University of Tennessee Health Science Center Memphis TN USA Estonian Genome Center University of Tartu Tartu Estonia Program in Medical and Population Genetics Broad Institute of Harvard and MIT Cambridge MA USA Department Clinical Sciences Malmö Lund University Malmö Sweden MRC Human Genetics Un

High blood pressure is a highly heritable and modifiable risk factor for cardiovascular disease. We report the largest genetic association study of blood pressure traits (systolic, diastolic and pulse pressure) to date in over 1 million people of European ancestry. We identify 535 novel blood pressure loci that not only offer new biological insights into blood pressure regulation but also highlight shared genetic architecture between blood pressure and lifestyle exposures. Our findings identify new biological pathways for blood pressure regulation with potential for improved cardiovascular disease prevention in the future.

关键词： Cardiovascular diseases Genome informatics Genome-wide association studies

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