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26th International World Wide Web Conference, WWW 2017 Companion

作者： Gonzalez-Beltran, Alejandra Peroni, Silvio Osborne, Francesco Vahdati, Sahar Oxford e-Research Centre University of Oxford Oxford United Kingdom Department of Computer Science and Engineering University of Bologna Bologna Italy Knowledge Media Institute Open University Milton Keynes United Kingdom Enterprise Information Systems University of Bonn Bonn Germany

ISBN: (纸本)9781450349147

The third edition of the Workshop on Semantics, Analytics and Visualisation: Enhancing Scholarly Data (SAVE-SD 2017) is taking place in Perth, Australia on the 3rd of April 2017, co-located with the 26th International World Wide Web Conference. The main goal of the workshop is to provide a venue for researchers, publishers and other companies to engage in discussions about semantics, analytics and vi-sualisations on scholarly data. © 2017 International World Wide Web Conference Committee (IW3C2), published under Creative Commons CC BY 4.0 License. WWW 2017, April 3-7, 2017, Perth, Australia.

关键词： World Wide Web

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Investigating different syntactic context types and context representations for learning word embeddings

Investigating different syntactic context types and context ...

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2017 Conference on Empirical Methods in Natural Language Processing, EMNLP 2017

作者： Li, Bofang Liu, Tao Zhao, Zhe Tang, Buzhou Drozd, Aleksandr Rogers, Anna Du, Xiaoyong School of Information Renmin University of China China Key Laboratory of Data Engineering and Knowledge Engineering MOE China Shenzhen Graduate School Harbin Institute of Technology China Global Scientific Information and Computing Center Tokyo Institute of Technology China Department of Computer Science University of Massachusetts Lowell United States

ISBN: (纸本)9781945626838

The number of word embedding models is growing every year. Most of them are based on the co-occurrence information of words and their contexts. However, it is still an open question what is the best definition of context. We provide a systematical investigation of 4 different syntactic context types and context representations for learning word embeddings. Comprehensive experiments are conducted to evaluate their effectiveness on 6 extrinsic and intrinsic tasks. We hope that this paper, along with the published code, would be helpful for choosing the best context type and representation for a given task. © 2017 Association for Computational Linguistics.

关键词： Embeddings

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Preface

OpenAccess Series in Informatics

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OpenAccess Series in Informatics 2019年 70卷 IX-X页

作者： Eskevich, Maria de Melo, Gerard Fäth, Christian McCrae, John P. Buitelaar, Paul Chiarcos, Christian Klimek, Bettina Dojchinovski, Milan CLARIN ERIC Utrecht Netherlands Department of Computer Science Rutgers University New BrunswickNJ United States Applied Computational Linguistics Goethe University Frankfurt Germany Insight Centre for Data Analytics National University of Ireland Galway Ireland Agile Knowledge Engineering and Semantic Web University of Leipzig Germany

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Keep Your Friends Close and Your Colleagues Nearby: The Hidden Ties That Improve STEM Education

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Change 2019年第1期51卷 42页

作者： Mestre, Jose P. Herman, Geoffrey L. Tomkin, Jonathan H. West, Matthew Jose P. Mestre (mestre@illinois.edu). A theoretical nuclear physicist by training Mestre’s research focuses on the learning of physics contributing in areas such as the acquisition and use of knowledge by experts and novices transfer of learning problem solving and instructional design. He has offered Congressional testimony on The Science of Learning has published numerous articles and books and is a Fellow of the American Physical Society.http://***/0000-0003-2110-1954 Geoffrey L. Herman (glherman@illinois.edu). Herman has a Ph.D. in Electrical and Computer Engineering and is a Teaching Assistant Professor in Computer Science and a Research Assistant Professor in the Department of Curriculum & Instruction at the University of Illinois. His research focuses on how students learn engineering and computing concepts and studying processes for creating systemic instructional change in college settings. Previously he was a postdoctoral researcher in Engineering Education at Purdue University.http://***/0000-0002-9501-2295 Jonathan H. Tomkin (tomkin@illinois.edu). Tomkin is a mathematically based geoscientist with two research focus areas: first he uses models and large data sets to determine how climates glaciers tectonics and landscapes interact. Second he explores how new technological and organizational approaches can improve STEM education. He produced the first geoscience MOOC is the editor of an open-source textbook and has published widely in both geoscience and STEM education. Matthew West (mwest@illinois.edu). Matthew West is an Associate Professor of Mechanical Science and Engineering at the University of Illinois with research interests in scientific computing that include time integration of deterministic and stochastic systems distributed computation and particle methods for simulation and estimation. In education he researches computer-based assessment and the development of innovative teaching cultures. Professor West is a University of Illinois Distinguished Teacher-Scholar and Colleg

A science department on the campus of the University of Illinois has received numerous national awards for excellence in undergraduate teaching. The secret to their success? For nearly two decades, they have collaboratively used evidence-based instructional practices (EBIP) in their introductory level courses. Despite these successes and efforts to spread their EBIP, no other departments followed this department's lead. Then, suddenly six years ago, many instructors from other departments began adopting EBIP in their classrooms. This article asks what was the catalyst for this change? Why had previous attempts at institutional change failed? The authors answer these questions by analyzing their efforts to transform the teaching practices in large-enrollment science and engineering introductory courses on their campus.

关键词： STEM Education Evidence Based Practice Teaching Methods Undergraduate Study College Faculty Educational Change Communities of Practice Mentors School CultureIllinois

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How China Deals with Big Data

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Annals of Data science 2017年第4期4卷 433-440页

作者： Shi, Yong Shan, Zhiguang Li, Jianping Fang, Yufei School of Economics and Management University of Chinese Academy of Sciences Beijing100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing China Informatization Research Department State Information Center Beijing100045 China Institute of Policy and Management Chinese Academy of Sciences Beijing100190 China School of Computer and Communication Engineering University of Science and Technology Beijing100083 China Informatization Research Department State Information Center Beijing100045 China

On September 5, 2015, the State Council of Chinese Government, China’s cabinet formally announced its Action Framework for Promoting Big Data (***, 2015). This is the milestone for China to catch up the global wave of big data. Since 2012 big data became a hot issue for scientific communities as well as the governments of many countries (Lazer et al. in science 343:1203–1205, 2014;Einav et al. in science 345:715, 2014;Cate in science 346:818, 2014;Khoury and Ioannidis in science 346:1054–1055, 2014). At the 2013 G8 Summit, the leaders of Canada, France, Germany, Italy, Japan, Russia, U.S.A. and United Kingdom agreed on an "open government plan" (***/government/publications/open-data-charter/g8-open-data-charter-and-technical-annex, 2013). China’s framework, however, mainly emphasizes the integration of all trans-departmental data and establishes a number of government-driven national big data platforms so as to provide big data services to research, public and enterprises. The framework not only demonstrates a strong commitment of the Chinese government on big data, but also covers a wide range of governmental branches, enterprises and institutions far more than that of other countries. In addition, the framework shows an interpretation of big data that differs from other countries. If its objective is achieved, China would become a strong "big data country". © 2017, Springer-Verlag GmbH Germany, part of Springer Nature.

关键词： Big data

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Iran in transition (vol 393, pg 1984, 2019)

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LANCET 2019年第10186期393卷 2124-2124页

作者： Danaei, G. Farzadfar, F. Kelishadi, R. [a]Department of Global Health and Population and Department of Epidemiology Harvard T H Chan School of Public Health Boston MA USA Department of Global Health and Population and Department of Epidemiology Harvard T H Chan School of Public Health Boston MA USA [b]Scientific Association for Public Health in Iran Boston MA USA Scientific Association for Public Health in Iran Boston MA USA [c]Non-Communicable Diseases Research Center Endocrinology and Metabolism Population Sciences Institute Tehran University of Medical Sciences Tehran Iran Non-Communicable Diseases Research Center Endocrinology and Metabolism Population Sciences Institute Tehran University of Medical Sciences Tehran Iran [d]Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Research Center Tehran University of Medical Sciences Tehran Iran [e]Diabetes Research Center Tehran University of Medical Sciences Tehran Iran Diabetes Research Center Tehran University of Medical Sciences Tehran Iran [f]Endocrinology and Metabolism Clinical Sciences Institute Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran Endocrinology and Metabolism Clinical Sciences Institute Department of Health Management and Economics Tehran University of Medical Sciences Tehran Iran [g]Department of Global Health and Public Policy Tehran University of Medical Sciences Tehran Iran Department of Global Health and Public Policy Tehran University of Medical Sciences Tehran Iran [h]Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran Department of Epidemiology and Biostatistics Tehran University of Medical Sciences Tehran Iran [i]School of Public Health Tehran University of Medical Sciences Tehran Iran School of Public Health Tehran University of Medical Sciences Tehran Iran [j]Faculty of Medicine Tehran University of Medical Sciences Tehran Iran Faculty of Medicine Te

Summary Being the second-largest country in the Middle East, Iran has a long history of civilisation during which several dynasties have been overthrown and established and health-related structures have been reorganised. Iran has had the replacement of traditional practices with modern medical treatments, emergence of multiple pioneer scientists and physicians with great contributions to the advancement of science, environmental and ecological changes in addition to large-scale natural disasters, epidemics of multiple communicable diseases, and the shift towards non-communicable diseases in recent decades. Given the lessons learnt from political instabilities in the past centuries and the approaches undertaken to overcome health challenges at the time, Iran has emerged as it is today. Iran is now a country with a population exceeding 80 million, mainly inhabiting urban regions, and has an increasing burden of non-communicable diseases, including cardiovascular diseases, hypertension, diabetes, malignancies, mental disorders, substance abuse, and road injuries.

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Prediction of Evaluation Value from Product Reviews and Explanations to Healthcare Products Using Network

Prediction of Evaluation Value from Product Reviews and Expl...

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2017 International MultiConference of Engineers and computer Scientists, IMECS 2017

作者： Sakaguchi, Ayumu Nohara, Shoji Saga, Ryosuke Department of Knowledge and Information Systems School of Sustainable System Sciences Osaka Prefecture University 1-1 Gakuen-cho Naka-ku Sakai Osaka Japan Department of the Computer Science and Intelligent Systems Graduate School of Engineering Osaka Prefecture University 1-1 Gakuen-cho Naka-ku Sakai Osaka Japan

ISBN: (纸本)9789881404732

Given that reviews are difficult to score, predicting evaluation values automatically can be useful. The evaluation value depends on users who buy certain products with known information that meet expectations. Numerous studies have already predicted the evaluation value from reviews. However, many of these studies only paid attention to user reviews, and the opinions of product providers were not considered. In this paper, we will comment about the keywords of reviews and explanations, create a co-occurrence network showing keywords, and perform multiple regression analysis using the features of the network. As a result, we can acquire results of high accuracy from multiple regression analysis to predict the value of products based on the reviews and explanations to the service.

关键词： Forecasting

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Corrections to “Toward Near-Ground Localization: Modeling and Applications for TOA Ranging Error” [Oct 17 5658-5662]

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IEEE Transactions on Antennas and Propagation 2018年第2期66卷 1052-1052页

作者： Cheng Xu Jie He Xiaotong Zhang Po-Hsuan Tseng Shihong Duan School of Computer and Communication Engineering University of Science and Technology Beijing and the Beijing Key Laboratory of Knowledge Engineering for Materials Science Beijing China Department of Electronic Engineering National Taipei University of Technology Taipei Taiwan

The authors of [1] would like to make the following corrections.

关键词： Antennas Distance measurement Time of arrival estimation Cramer-Rao bounds

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MRI-based surgical planning for lumbar spinal stenosis 20th

MRI-based surgical planning for lumbar spinal stenosis

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20th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2017

作者： Abbati, Gabriele Bauer, Stefan Winklhofer, Sebastian Schüffler, Peter J. Held, Ulrike Burgstaller, Jakob M. Steurer, Johann Buhmann, Joachim M. Department of Engineering Science University of Oxford Oxford United Kingdom Department of Computer Science ETH Zürich Zürich Switzerland Neuroradiology University Hospital Zürich Zürich Switzerland Computational Pathology Memorial Sloan Kettering Cancer Center New York United States Horten Centre for Patient Oriented Research and Knowledge Transfer University of Zürich Zürich Switzerland

ISBN: (纸本)9783319661780

The most common reason for spinal surgery in elderly patients is lumbar spinal stenosis (LSS). For LSS, treatment decisions based on clinical and radiological information as well as personal experience of the surgeon show large variance. Thus a standardized support system is of high value for a more objective and reproducible decision. In this work, we develop an automated algorithm to localize the stenosis causing the symptoms of the patient in magnetic resonance imaging (MRI). With 22 MRI features of each of five spinal levels of 321 patients, we show it is possible to predict the location of lesion triggering the symptoms. To support this hypothesis, we conduct an automated analysis of labeled and unlabeled MRI scans extracted from 788 patients. We confirm quantitatively the importance of radiological information and provide an algorithmic pipeline for working with raw MRI scans. Both code and data are provided for further research at ***. © Springer International Publishing AG 2017.

关键词： Magnetic resonance imaging

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Taxonomy of digital forensics: Investigation tools and challenges

arXiv

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arXiv 2017年

作者： Rana, Nikita Sansanwal, Gunjan Khatter, Kiran Singh, Sukhdev Department of Computer Science and Engineering Manav Rachna International University Faridabad121004 India Accendere Knowledge Management Services Pvt. Ltd India

In today's world of computers, any kind of information can be made available within few clicks for different endeavours. The information may be tampered by changing the statistical properties and can be further used for criminal activities. These days, Cybercrimes are happening at a very large scale, and possess big threats to the security of an individual, firm, industry and even to developed countries. To combat such crimes, law enforcement agencies and investment institutions are incorporating supportive examination policies, procedures and protocols to address the complete investigation process. The paper entails a detailed review of several cybercrimes followed by various digital forensics processes involved in the cybercrime investigation. Further various digital forensics tools with detail explanation are discussed with their advantages, disadvantages, challenges, and drawbacks. A comparison among all the selected tools is also presented. Finally the paper recommends the need of training programs for the first responder and judgement of signature based image authentication. Copyright © 2017, The Authors. All rights reserved.

关键词： Electronic crime countermeasures

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