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arXiv 2019年

作者： Bai, Hongxiao Zhao, Hai Zhao, Junhan Department of Computer Science and Engineering Shanghai Jiao Tong University Key Lab. of Shanghai Education Commission for Intelligent Interaction and Cognitive Engineering Shanghai Jiao Tong University Shanghai China MoE Key Lab of Artificial Intelligence Ai Institute Shanghai Jiao Tong University Computer Graphics Technology Purdue University West LafayetteIN United States

Implicit discourse relation recognition is a challenging task due to the absence of the nec-essary informative clue from explicit connec-tives. The prediction of relations requires a deep understanding of the semantic meanings of sentence pairs. As implicit discourse relation recognizer has to carefully tackle the se-mantic similarity of the given sentence pairs and the severe data sparsity issue exists in the meantime, it is supposed to be beneficial from mastering the entire training data. Thus in this paper, we propose a novel memory mecha-nism to tackle the challenges for further performance improvement. The memory mecha-nism is adequately memorizing information by pairing representations and discourse relations of all training instances, which right fills the slot of the data-hungry issue in the current im-plicit discourse relation recognizer. Our experiments show that our full model with memo-rizing the entire training set reaches new state-of-the-art against strong baselines, which es-pecially for the first time exceeds the milestone of 60% accuracy in the 4-way task. Copyright © 2019, The Authors. All rights reserved.

关键词： Semantics

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Sparse weighted naive bayes classifier for efficient classification of categorical data 3

Sparse weighted naive bayes classifier for efficient classif...

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3rd IEEE International Conference on Data Science in Cyberspace, DSC 2018

作者： Zheng, Zhuoyuan Cai, Yunpeng Yang, Yujie Li, Ye Guangxi Key Laboratory of Trusted Software Guangxi Colleges and Universities Key Lab. of Intelligent Processing of Computer Images and Graphics Guilin University of Electronic Technology Guilin541004 China Shenzhen Institutes of Advanced Technology Key Laboratory for Biomedical Informatics and Health Engineering Chinese Academy of Sciences Shenzhen518055 China

ISBN: (纸本)9781538642108

Feature selection has become a key challenge in machine learning with the rapid growth of data size in real-world applications. However, existing feature selection methods mainly focus on numeric data, which will lead to quality loss when handling classification problems involving categorical variables. In this paper, we proposed an improvement of Bayesian Classifier with the sparse regression technology. To the best of our knowledge, this is the first attempt to extend sparse regression for directly process of categorical variables. We implemented the idea for the case of weighted naive Bayes classifier. The introduction of L1 regularized learning ensures the algorithm to retain only a minimal subset of variables for model building, while at the same time achieves a near-optimal decision hyper-plane, which leads to excellent performance in case of high dimensional or small sample size situations. We carried out benchmark test on five UCI benchmark categorical data sets, which proved that the proposed algorithm have competitive performances over the original weighted naive bayes classifier and several state-of-the-art feature selection methods including L1 logistic regression and SVM-RFE. © 2018 IEEE.

关键词： Feature Selection

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Evaluate the gray code in distributed fields for tracking

International Journal of Signal Processing, Image Processing...

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International Journal of Signal Processing, Image Processing and Pattern Recognition 2016年第11期9卷 37-44页

作者： Wu, Xianyun Liu, Kai Cao, Jinyan Li, Yunsong Wang, Li State Key Lab. of Integrated Service Networks Xidian University Xi’an China School of Computer Science and Technology Xidian University Xi’an China Xidian University China

Distribution Fields (DFs) for tracking achieved a better performance than traditional algorithms due to its special representation that allows smoothing the objective function without destroying information about pixel values. DFs descriptor can satisfy both the specificity and smooth landscape requirements of a good tracking algorithm. In this paper, we evaluate the Gray code in original DFs algorithm by replacing the pixel values using Gray code instead of original binary code. Experimental results show that the Gray code can improve the tracking efficiency in certain way. © 2016 SERSC.

关键词： Pixels

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Adaptive Enterprise Architecture for the Future: Towards a Reconceptualization of EA

Adaptive Enterprise Architecture for the Future: Towards a R...

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IEEE Conference on Commerce and Enterprise Computing, CEC

作者： Janne J. Korhonen James Lapalme Doug McDavid Asif Q. Gill Department of Computer Science School of Science Aalto University Helsinki Finland Ecole de Technol. Super. Numerix Res. Lab. Oper. & Logistics Eng. Montreal QC Canada International Society of Service Innovation Professionals Sacramento CA USA School of Software University of Technology Sydney Sydney Australia

In some conventional definitions, Enterprise Architecture (EA) is conceived as a descriptive overview of the enterprise, while in other views EA is seen as a prescriptive framework of principles and models that helps translate business strategy to enterprise change. The conceptualizations of EA also vary in scope. There is an increasing recognition of EA as a systemic, enterprise-wide capability encompassing all relevant facets of the organization, transcending the traditional IT-centric view. However, we argue that none of the conventional conceptualizations of EA are adaptive in the face of today's complex environment. We view that an adaptive EA must go beyond a single organization and fully appreciate enterprise-in-environment ecosystemic perspective. Drawing on the heritage of Open Socio-Technical Systems Design and adopting the "three schools of thought" as a meta-paradigmatic backdrop, the paper features four different views of long-time scholar-practitioners, who discuss what an adaptive enterprise architecture would entail. Integration of these views paints a radically reconceptualized picture of enterprise architecture for the future. With this paper, we want to lay a foundation for a debate on the need for alternative conceptualizations, manifestations and research agenda for enterprise architecture.

关键词： computer architecture Organizations Coherence Context Biological system modeling Complexity theory

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5G entering into a new era [Guest Editorial]

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China Communications 2017年第12期14卷 iv-vi页

作者： Feifei Gao Changle Li Jun Fang Kaizhi Huang Zhi Quan Chengwen Xing Jianhua Zhang Zhongshan Zhang Liqiang Zhao Yulong Zou Department of Automation Tsinghua University Beijing China State Key Laboratory of Integrated Services Networks Xidian University University of Eletronic Science and Technology of China National Digital Switching System Engineering & Technological Research Center Zhengzhou China College of Information Engineering Shenzhen University School of Information and Electronics Beijing Institute of Technology Beijing University of Posts and Telecommunication School of Computer and Communication Engineering in the University of Science and Technology Beijing State Key Lab. of Integrated Service Networks Xidian University Nanjing University of Posts and Telecommunications (NUPT) Nanjing China

The ever increasing wireless data services, such as imaging, video, audio, multimedia, etc., have demands for the very high speed wireless communications and network, which are unfortunately a bottleneck when combining with the wireline core network. Users' are now expecting high quality of experience with low-cost devices, ubiquitous connectivity, energy efficiency, high reliability, or even ultra-low latency if a vehicle terminal is applied.

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Constructing Multiple Scene Graphs in Distributed Environment

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computer Aided Drafting,Design and Manufacturing 2015年第1期25卷 16-21页

作者： XIA Rui WANG Guo-ping LI Sheng WANG Heng Shenzhen Key Lab for Cloud Computing Technology and Applications Shenzhen Graduate School of Peking University Graphics & Interaction Lab. School of Electronics Engineering and Computer SciencesPeking University Beijing Engineering Technology Research Center of Virtual Simulation and Visualization Peking University

Scene graph is a infrastructure of the virtual reality system to organize the virtual scene with abstraction, it can provide facility for the rendering engine and should be integrated effectively on demand into a real-time system, where a large quantities of scene objects and resources can be manipulated and managed with high flexibility and reliability. We present a new scheme of multiple scene graphs to accommodate the features of rendering engine and distributed systems. Based upon that, some other functions, e.g. block query, interactive editing, permission management, instance response, ＂redo＂ and ＂undo＂, are implemented to satisfy various requirements. At the same time, our design has compatibility to popular C/S architecture with good concurrent performance. Above all, it is convenient to be used for further development. The results of experiments including responding time demonstrate its good performance.

关键词： multiple scene graphs authority scene editing distributed systems

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Preface

Proceedings of the 11th European Conference on Games Based L...

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Proceedings of the 11th European Conference on Games Based Learning, ECGBL 2017 2017年 viii-x页

作者： Pivec, Maja Gründler, Josef Admiraal, Wilfried Alemi, Minoo All, Anissa Almeida, Ana Amresh, Ashish Arnab, Sylvester Ask, Kristine Avouris, Nikolaos Awwal, Nafisa Hauge, Jannicke Baalsrud Badau, Dana Barata, Ana Barendregt, Wolmet Basaiawmoit, Rajiv Bellotti, Francesco Blanchfield, Peter Borit, Melania Boskic, Natasha Boyle, Liz Brady, Mairead Bratitsis, Tharrenos Brinch, Sara Brom, Cyril Brooks, Anthony Brown, David Brox, Ellen Busch, Carsten Caldeira, Carlos Callies, Sophie Cardoso, Tiago Carron, Thibault Casimir, Rommert De Castro, António Vieira Chang, Maiga Charalambis, Dimitris Charles, Darryl Charlier, Nathalie Chee, Yam San Chen, Ming-Puu Chiarello, Fabio Connolly, Thomas Crockett, Larry Darwish, Tamer Sigurdardottir, Helga Deliyannis, Ioannis Demirbilek, Muhammet Sigurdardottir, Helga Dis Duin, Heiko Dyer, Ronald Edgar, David Ejsing-Duun, Stine Escudeiro, Paula Felicia, Patrick Fesakis, Georgios Figueira, Ana Paula Fotaris, Panagiotis Fujimoto, Toru George, Sebastien Georgiadis, Panagiotis Gerodetti, Natalia Giannakoulopoulos, Andreas Gjedde, Lisa Goebel, Stefan Gomez-Martin, Pedro Pablo Gouscos, Dimitris Grigoriadou, Maria Guralnick, David Guttormsgaard, Vibeke Habgood, Jacob Hainey, O. Hanghoj, Thorkild Hawlitschek, Anja Hemben, Terseer Hlavacs, Helmut Hommedal, Silje Hole Hollins, Paul Idrus, Rozhan Wang, Alf Inge Ismail, Marina Jans, Ruben Juzeleniene, Saule Kalavassis, Fragiskos Kalogiannakis, Michail Karakostas, Anastasios Katzlinger-Felhofer, Elisabeth Ketamo, Harri Ketelhut, Diane Jass Kickmeier-Rust, Michael Kiili, Kristian Koeppen, Veit Kolås, Line Kordaki, Maria Korkut, Safak Kourti, Evangelia Li, Ken Lukosch, Heide MaCleod, Hamish Magnussen, Rikke Majgaard, Gunver Marchetti, Emanuela Marques, Bertil Marty, Jean-Charles Marzantowicz, Lukasz Mehm, Florian Meimaris, Michail Michel, Christine Moffat, David Montero-Fleta, Begoña Moseley, Alexander Mota, Dulce Mozelius, Peter Nadolski, Rob Nelson, Brian Neville, Karen Ng, Annie W.Y. Nixon, Darren Nocchi, Susanna Broin, Daire O. O'Mullane, John Skev Leiden University Leiden Netherlands Sharif University of Technology Iran IMinds-MICT-Ghent University Belgi Belgium Universidade de Coimbra Portugal Arizona State University United States Coventry University United Kingdom Norway University of Patras Greece University of Melbourne Australia Bremer Institut for Produktion und Logistik Germany University of Medicine and Pharmacy of Targu Mures Romania Portugal Gothenburg University Department of Applied IT Sweden Aarhus University Denmark University of Genoa Italy School of Computer Science University of Nottingham United Kingdom UiT - The Arctic Univeristy of Norway University of Troms Norway University of British Columbia Canada Univesity of the West of Scotland United Kingdom Open University of Cyprus Greece ESCP Europe France Trinity College Dublin Ireland University of Western Macedonia Greece KDU University College Malaysia Charles University Prague Czech Republic Aalborg University Denmark Nottingham Trent University United Kingdom Nord-Trøndelag University College Steinkjer Norway University of Applied Sciences HTW-Berlin Germany University of Evora Portugal UQAM Canada Universidade Nova de Lisboa Portugal LIP6 - Paris Université de Savoie France Tilburg University Netherlands Open University of the Natherlands Nederland United States Athabasca University Canada University of Athens Greece University of Ulster United Kingdom Catholic University of Leuven Belgium Nanyang Technological University Singapore Singapore National Taiwan Normal University Taiwan Italy University of West of Scotland United Kingdom Augsburg College United States Brunel University United Kingdom Ionian University Greece Suleyman Demirel University Turkey Glamorgan University United Kingdom BIBA - Bremer Institut for Produktion und Logistik GmbH Germany Managment School University of Liverpool United Kingdom Glasgow Caledonian University United Kingdom Aalborg Univ. Copenhagen Denmark Portugal Waterford Institute of

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Research on Simulation technology Application on Higher Education for Deaf/hard-of-hearing Students in China

Research on Simulation Technology Application on Higher Educ...

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2014 3rd International Conference on Science and Social Research

作者： Dengfeng Yao Zhili Liu Junxia Yan Yunfeng Qiu Beijing Key Laboratory of Information Service Engineering Beijing Union University Lab. of Computational Linguistics School of HumanitiesTsinghua University Special Education College Beijing Union University College of Computer Wuhan Vocational College of Software and Engineering Foreign Language College Jing Chu University of Science and Technology

In teaching of computer language, how can we improve their hearing of hearing-impaired students featured with special physiological characteristics and reduce the inconvenience and obstacles caused during teaching knowledge in the most effective way? In this research, we have applied simulation technology and developed the teaching simulation platform for them, and it is practically demonstrated in the hearing-impaired students in higher education and the application of research result that the system works well, with intuitive, efficient, and other characteristics, a strong promotion of the college teaching model changes, the language learning, education teaching and research referred.

关键词： robot simulation deaf/hard-of-hearing students educational technology

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Incremental collab.rative filtering based on Mahalanobis distance and fuzzy membership for recommender systems

Incremental collaborative filtering based on Mahalanobis dis...

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作者： Komkhao, Maytiyanin Lu, Jie Li, Zhong Halang, Wolfgang A. Department of Computer Engineering Fernuniversitt in Hagen Hagen Germany Decision Systems and E-Service Intelligence Lab. School of Software University of Technology Sydney Sydney Australia

Recommender systems, as an effective personalization approach, can suggest best-suited items (products or services) to particular users based on their explicit and implicit preferences by applying information filtering technology. Collab.rative filtering (CF) method is currently the most popular and widely adopted recommendation approach. It works by collecting user ratings for items in a given domain and by computing the similarity between the profiles of several users in order to recommend items. Current similarity measures and models updated by traditional model-based CF have, however, shortcomings with respect to accuracy of prediction and scalab.lity of recommender systems. To overcome these problems, here an incremental CF algorithm based on the Mahalanobis distance is presented. The algorithm has two phases: the learning phase, in which models of similar users are constructed incrementally, and the prediction phase, in which interested users are clustered by measuring their similarity to existing clusters in a model. To handle confusion of decision making on overlapping clusters, fuzzy sets are employed, and the degree of membership to them is expressed by the Mahalanobis radial basis function. Experimental results demonstrate that the proposed algorithm leads to improved prediction accuracy and prevents the scalab.lity problem in recommendation systems. © 2013 Copyright Taylor and Francis Group, LLC.

关键词： Fuzzy sets

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An innovative approach for automatically grading spelling in essays using rubric-based scoring

An innovative approach for automatically grading spelling in...

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作者： Fazal, Anhar Hussain, Farookh Khadeer Dillon, Tharam S. School of Information Systems Curtin University of Technology Perth WA Australia Decision Support and E-Service Intelligence Lab. School of Software University of Technology Sydney NSW Australia Department of Computer Science and Computer Engineering La Trobe University Melbourne VIC Australia

Automated Essay Grading (AEG) is defined as a computer technology that evaluates and scores written prose. A number of AEG systems have been developed since the 1960s and in most of them, an ad-hoc or generalized approach is used to grade spelling even though it is an important element of an essay-scoring rubric. Existing approaches do not therefore give an accurate representation or measure of spelling in essays. According to the rubric-based scoring method used in the National Assessment Program "Literacy and Numeracy (NAPLAN) in Australia, spelling is marked in three steps" first, by identifying the correct and incorrect words in the essay;second, by categorizing each word based on the difficulty level into one of four classes: Simple, Common, Difficult or Challenging, and counting the number of correct and incorrect words in each category;finally, by using the pre-defined NAPLAN rubric scale to assign the mark. Only a small number of existing AEG systems can be used for rubric-based scoring, and none can be used to grade spelling according to the NAPLAN rubric. In this paper, we address this shortcoming in the existing literature and present an innovative approach to automatically mark spelling using rubric based scoring. We develop two algorithms based on the rules and heuristics of the English language to formulize the rubric for spelling and then implement these algorithms in Java language and perform a series of evaluations of our system using an essay dataset. Our results are very promising, even though it is the first system of this kind.

关键词： Grading

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