检索结果-内蒙古大学图书馆

International Joint Conference on Neural Networks, IJCNN 2015

作者： Costa, Bruno Sielly Jales Bezerra, Clauber Gomes Guedes, Luiz Affonso Angelov, Plamen Parvanov Campus Natal - Zona Norte Federal Institute of Rio Grande Do Norte - IFRN Natal Brazil Campus EaD Federal Institute of Rio Grande Do Norte - IFRN Natal Brazil Department of Computer Engineering and Automation Federal University of Rio Grande Do Norte - UFRN Brazil Lancaster University Data Science Group School of Computing and Communications LancasterLA1 4WA United Kingdom Excellence Carlos III University Madrid Spain

ISBN: (纸本)9781479919604

Fault detection is a task of major importance in industry nowadays, since that it can considerably reduce the risk of accidents involving human lives, in addition to production and, consequently, financial losses. Therefore, fault detection systems have been largely studied in the past few years, resulting in many different methods and approaches to solve such problem. This paper presents a detailed study on fault detection on industrial processes based on the recently introduced eccentricity and typicality data analytics (TEDA) approach. TEDA is a recursive and non-parametric method, firstly proposed to the general problem of anomaly detection on data streams. It is based on the measures of data density and proximity from each read data point to the analyzed data set. TEDA is an online autonomous learning algorithm that does not require a priori knowledge about the process, is completely free of user- and problem-defined parameters, requires very low computational effort and, thus, is very suitable for real-time applications. The results further presented were generated by the application of TEDA to a pilot plant for industrial process. © 2015 IEEE.

关键词： Fault detection

来源：评论

学校读者我要写书评

暂无评论

Personalized Financial News Recommendation Algorithm Based on Ontology

引用

Procedia Computer science 2015年 55卷 843-851页

作者： Rui Ren Lingling Zhang Limeng Cui Bo Deng Yong Shi School of Management University of Chinese Academy of Sciences Beijing 100190 China Key Laboratory of Big Data Mining and Knowledge Management Chinese Academy of Sciences Beijing 100190 China Research Centre on Fictitious Economy and Data Science Chinese Academy of Sciences Beijing 100190 China School of Computer and Control Engineering University of Chinese Academy of Sciences Beijing 100190 China Institute of Computing Technology Chinese Academy of Sciences Beijing 100190 China

To deal with the challenge of information overload, in this paper, we propose a financial news recommendation algorithm which help users find the articles that are interesting to read. To settle the ambiguity problem, a new presented OF-IDF method is employed to represent the unstructured text data in the form of key concepts, synonyms and synsets which are all stored in the domain ontology. For users, the recommendation algorithm build the profiles based on their behaviors to detect the genuine interests and predict current interests automatically and in real time by applying the thinking of relevance feedback. Finally, the experiment conducted on a financial news dataset demonstrates that the proposed algorithm significantly outperforms the performance of a traditional recommender.

关键词： news recommendation algorithm ontology relevence feedback OF-IDF

来源：评论

学校读者我要写书评

暂无评论

Characterizing Multi-media Retrieval Applications

Characterizing Multi-media Retrieval Applications

引用

International Conference on Parallel Processing (ICPP)

作者： Yunping Lu Xin Wang Weihua Zhang Yi Li Wenyun Zhao Shanghai Key Laboratory of Data Science Fudan University Shanghai China State Key Lab of Mathematical Engineering and Advanced Computing Wuxi China Software School Fudan University Shanghai China Parallel Processing Institute Fudan University Shanghai China

Multimedia data, especially image and video data, have become one of the most overwhelming data types on the Internet recently. Considering the user experience and real application requirements, multimedia data always demand a real-time processing speed. As a result, the huge amount of such data make retrieving useful information from them not only data-intensive, but also computation-intensive, which poses significant challenges to current system and architecture designs. Unfortunately, most prior studies focus only on text based retrieval systems or traditional multimedia processing applications. As far as we know, there is no systematic study on analyzing the characteristics of multimedia retrieval applications and how they might impact system and architecture designs. In this paper, we make the first attempt to construct a multimedia retrieval benchmark suite (called MMR Bench) to evaluate the corresponding system and architecture designs. To embody diverse multimedia retrieval applications, we collect eight state-of-the-art multimedia retrieval algorithms which cover the whole retrieval stages, including feature extraction, feature matching, and spatial verification. To satisfy diverse evaluation purposes, we implement multiple versions for each algorithm, including sequential version, pthread version for multi-core evaluation and data-parallel (i.e., Map-reduce) version for data-center evaluation. Moreover, MMR Bench provides flexible interfaces through retrieval stages, as well as a tool to adjust parameters and regenerating different scales of reasonable input. With such a flexible design, the algorithms in MMR Bench may be not only suitable for individual kernel-level evaluation, but also capable to be integrated into a complete infrastructure for system-level evaluation. Based on MMR Bench, we further analyze the inherent architectural characteristics, such as input size sensitivity and workload balance, which provides some insights into system and archite

关键词： Multimedia communication Feature extraction Benchmark testing Streaming media Algorithm design and analysis Computer architecture

来源：评论

学校读者我要写书评

暂无评论

Cover Image, Volume 84, Issue 7

引用

Proteins: Structure, Function, and Bioinformatics 2016年第7期84卷

作者： Wei Wang Juan Liu Lin Sun Department of Computer Science and Technology College of Computer and Information Engineering Henan Normal University Xinxiang 453007 China Laboratory of Computation Intelligence and Information Processing Engineering Technology Research Center for Computing Intelligence and Data Mining Henan Province China Institute of Computer Software School of Computer Wuhan University Wuhan 430072 China

来源：评论

学校读者我要写书评

暂无评论

Multivariate spearman's ρ for aggregating ranks using copulas

The Journal of Machine Learning Research

引用

The Journal of Machine Learning Research 2016年第1期17卷

作者： Kevin Murphy Bernhard Schölkopf Justin Bedö Cheng Soon Ong Google MPI for Intelligent Systems The Walter and Eliza Hall Institute Victoria Australia and The Department of Computing and Information Systems The University of Melbourne VIC Australia Data61 CSIRO Canberra ACT Australia and Research School of Computer Science The Australian National University Australia and The Department of Electrical and Electronic Engineering The University of Melbourne VIC Australia

We study the problem of rank aggregation: given a set of ranked lists, we want to form a consensus ranking. Furthermore, we consider the case of extreme lists: i.e., only the rank of the best or worst elements are known. We impute missing ranks and generalise Spearman's ρ to extreme ranks. Our main contribution is the derivation of a non-parametric estimator for rank aggregation based on multivariate extensions of Spearman's ρ, which measures correlation between a set of ranked lists. Multivariate Spearman's ρ is defined using copulas, and we show that the geometric mean of normalised ranks maximises multivariate correlation. Motivated by this, we propose a weighted geometric mean approach for learning to rank which has a closed form least squares solution. When only the best (top-k) or worst (bottom-k) elements of a ranked list are known, we impute the missing ranks by the average value, allowing us to apply Spearman's ρ. We discuss an optimistic and pessimistic imputation of missing values, which respectively maximise and minimise correlation, and show its effect on aggregating university rankings. Finally, we demonstrate good performance on the rank aggregation benchmarks MQ2007 and MQ2008.

关键词：

来源：评论

学校读者我要写书评

暂无评论

Search for Cosmic-Ray Electron and Positron Anisotropies with Seven Years of Fermi Large Area Telescope data

引用

Physical Review Letters 2017年第9期118卷 091103-091103页

作者： S. Abdollahi M. Ackermann M. Ajello A. Albert W. B. Atwood L. Baldini G. Barbiellini R. Bellazzini E. Bissaldi E. D. Bloom R. Bonino E. Bottacini T. J. Brandt P. Bruel S. Buson M. Caragiulo E. Cavazzuti A. Chekhtman S. Ciprini F. Costanza A. Cuoco S. Cutini F. D’Ammando F. de Palma R. Desiante S. W. Digel N. Di Lalla M. Di Mauro L. Di Venere B. Donaggio P. S. Drell C. Favuzzi W. B. Focke Y. Fukazawa S. Funk P. Fusco F. Gargano D. Gasparrini N. Giglietto F. Giordano M. Giroletti D. Green S. Guiriec A. K. Harding T. Jogler G. Jóhannesson T. Kamae M. Kuss S. Larsson L. Latronico J. Li F. Longo F. Loparco P. Lubrano J. D. Magill D. Malyshev A. Manfreda M. N. Mazziotta M. Meehan P. F. Michelson W. Mitthumsiri T. Mizuno A. A. Moiseev M. E. Monzani A. Morselli M. Negro E. Nuss T. Ohsugi N. Omodei D. Paneque J. S. Perkins M. Pesce-Rollins F. Piron G. Pivato G. Principe S. Rainò R. Rando M. Razzano A. Reimer O. Reimer C. Sgrò D. Simone E. J. Siskind F. Spada G. Spandre P. Spinelli A. W. Strong H. Tajima J. B. Thayer D. F. Torres E. Troja J. Vandenbroucke G. Zaharijas S. Zimmer Department of Physical Sciences Hiroshima University Higashi-Hiroshima Hiroshima 739-8526 Japan Deutsches Elektronen Synchrotron DESY D-15738 Zeuthen Germany Department of Physics and Astronomy Clemson University Kinard Lab of Physics Clemson South Carolina 29634-0978 USA Los Alamos National Laboratory Los Alamos New Mexico 87545 USA Santa Cruz Institute for Particle Physics Department of Physics and Department of Astronomy and Astrophysics University of California at Santa Cruz Santa Cruz California 95064 USA Dipartimento di Fisica “Enrico Fermi” dell’Università di Pisa I-56126 Pisa Italy Istituto Nazionale di Fisica Nucleare Sezione di Pisa I-56127 Pisa Italy Istituto Nazionale di Fisica Nucleare Sezione di Trieste I-34127 Trieste Italy Dipartimento di Fisica Università di Trieste I-34127 Trieste Italy Dipartimento di Fisica “M. Merlin” dell’Università e del Politecnico di Bari I-70126 Bari Italy Istituto Nazionale di Fisica Nucleare Sezione di Bari I-70126 Bari Italy W. W. Hansen Experimental Physics Laboratory Kavli Institute for Particle Astrophysics and Cosmology Department of Physics and SLAC National Accelerator Laboratory Stanford University Stanford California 94305 USA Istituto Nazionale di Fisica Nucleare Sezione di Torino I-10125 Torino Italy Dipartimento di Fisica Università degli Studi di Torino I-10125 Torino Italy NASA Goddard Space Flight Center Greenbelt Maryland 20771 USA Laboratoire Leprince-Ringuet École polytechnique CNRS/IN2P3 F-91128 Palaiseau France Agenzia Spaziale Italiana (ASI) Science Data Center I-00133 Roma Italy College of Science George Mason University Fairfax Virginia 22030 USA resident at Naval Research Laboratory Washington DC 20375 USA Istituto Nazionale di Fisica Nucleare Sezione di Perugia I-06123 Perugia Italy Institute for Theoretical Particle Physics and Cosmology (TTK) RWTH Aachen University D-52056 Aachen Germany INAF Istituto di Radioastronomia I-40129 Bologna Italy Dipartimento di Astronomia Un

The Large Area Telescope on board the Fermi Gamma-ray Space Telescope has collected the largest ever sample of high-energy cosmic-ray electron and positron events since the beginning of its operation. Potential anisotropies in the arrival directions of cosmic-ray electrons or positrons could be a signature of the presence of nearby sources. We use almost seven years of data with energies above 42 GeV processed with the Pass 8 reconstruction. The present data sample can probe dipole anisotropies down to a level of 10−3. We take into account systematic effects that could mimic true anisotropies at this level. We present a detailed study of the event selection optimization of the cosmic-ray electrons and positrons to be used for anisotropy searches. Since no significant anisotropies have been detected on any angular scale, we present upper limits on the dipole anisotropy. The present constraints are among the strongest to date probing the presence of nearby young and middle-aged sources.

关键词： Cosmic ray & astroparticle detectors Cosmic ray propagation Cosmic ray sources Cosmological parameters

来源：评论

学校读者我要写书评

暂无评论

Online fault detection based on Typicality and Eccentricity data Analytics

Online fault detection based on Typicality and Eccentricity ...

引用

International Joint Conference on Neural Networks (IJCNN)

作者： Bruno Sielly Jales Costa Clauber Gomes Bezerra Luiz Affonso Guedes Plamen Parvanov Angelov Campus Natal - Zona Norte Federal Institute of Rio Grande do Norte - IFRN Brazil Campus EaD Federal Institute of Rio Grande do Norte - IFRN Natal Brazil Federal University of Rio Grande do Norte - UFRN Chair of Excellence Carlos III University Madrid Spain Data Science Group School of Computing and Communications Lancaster University Lancaster United Kingdom

ISBN: (纸本)9781479919611

关键词： Online Fault Detection Based Typicality Eccentricity data Analytics Defect detection Industrial processes anomaly detection Eccentricity ECCENTRIC read data pilot plants Fault detection system Recursive Accidents

来源：评论

学校读者我要写书评

暂无评论

On the privacy-conscientious use of mobile phone data

引用

Scientific data 2018年第1期5卷 180286页

作者： Yves-Alexandre de Montjoye Sébastien Gambs Vincent Blondel Geoffrey Canright Nicolas de Cordes Sébastien Deletaille Kenth Engø-Monsen Manuel Garcia-Herranz Jake Kendall Cameron Kerry Gautier Krings Emmanuel Letouzé Miguel Luengo-Oroz Nuria Oliver Luc Rocher Alex Rutherford Zbigniew Smoreda Jessica Steele Erik Wetter Alex Sandy Pentland Linus Bengtsson Department of Computing Imperial College London London SW7 2AZ UK. MIT Media Lab 20 Ames St Cambridge MA 02139 USA. Université du Québec à Montréal Département d'informatique Case postale 8888 succ. Centre-ville Montréal (Québec) H3C 3P8 Canada. Université catholique de Louvain Place de l'Université 1 1348 Louvain-la-Neuve Belgium. Telenor Research Snarøyveien 30 1360 Fornebu Norway. Orange 44 avenue de la République 92320 Châtillon France. Riaktr 5 Place du Champs de Mars 1050 Brussels Belgium. UNICEF Office of Innovation 3 UN Plaza New York NY 10017 USA. University of Washington Dept. of Computer Science 708b 11th Avenue East Seattle WA 98102 USA. Data-Pop Alliance 99 Madison Avenue 15th Floor New York NY 10016 USA. UN Global Pulse 370 Lexington Avenue New York NY 10017 USA. Vodafone Research Paddington Central London W2 6BY UK. University of Southampton Geography and Environment Building 44 University Road Southampton SO17 1BJ UK. Flowminder Foundation Roslagsgatan 17 SE-11355 Stockholm Sweden. Stockholm School of Economics Sveavägen 65 113 83 Stockholm Sweden. Asian Institute of Management 123 Paseo de Roxas 1229 Metro Manila Philippines.

来源：评论

学校读者我要写书评

暂无评论

Reports of the AAAI 2014 conference workshops

Reports of the AAAI 2014 conference workshops

引用

作者： Albrecht, Stefano V. Barreto, André M. S. Braziunas, Darius Buckeridge, David L. Cuayáhuitl, Heriberto Dethlefs, Nina Endres, Markus Farahmand, Amir-Massoud Fox, Mark Frommberger, Lutz Ganzfried, Sam Guillet, Sébastien Gil, Yolanda Hunter, Lawrence E. Jhala, Arnav Kersting, Kristian Konidaris, George Lecue, Freddy McIlraith, Sheila Natarajan, Sriraam Noorian, Zeinab Poole, David Ronfard, Rémi Saffiotti, Alessandro Shaban-Nejad, Arash Srivastava, Biplav Tesauro, Gerald Uceda-Sosa, Rosario Van Den Broeck, Guy Van Otterlo, Martijn Wallace, Byron C. Weng, Paul Wiens, Jenna Zhang, Jie School of Informatics University of Edinburgh United Kingdom Department of Applied and Computational Mathematics Brazilian National Laboratory Brazil Big Data Group Kobo Inc. Brazil Department of Epidemiology and Biostatistics McGill University Canada School of Mathematical and Computer Sciences Heriot-Watt University in Edinburgh United Kingdom University of Augsburg Germany Carnegie Mellon University United States University of Toronto Canada Cognitive Systems Group University of Bremen Germany LIARA UQAC Chicoutimi Canada Information Sciences Institute University of Southern California Computer Science Department United States Center for Computational Pharmacology University of Colorado School of Medicine United States Department of Computational Media University of California Santa Cruz United States Computer Science Department Technical University of Dortmund Germany MIT Computer Science and Artificial Intelligence Laboratory CambridgeMA United States IBM Research - Smarter Cities Technology Centre Dubline Ireland School of Informatics and Computing Indiana University United States Department of Computer Science University of Saskatchewan Canada University of British Columbia Canada INRIA University of Grenoble France Orebro University Sweden McGill Clinical and Health Informatics Group McGill University Canada IBM Research United States Cognitive Computing Department IBM Research Yorktown HeightsNY United States Computer Science Department Katholieke Universiteit Leuven Belgium Cognitive Artificial Intelligence Department Radboud University Nijmegen Netherlands University of Texas Austin United States Pierre and Marie Curie University Paris France University of Michigan United States School of Computer Engineering Nanyang Technological University Singapore

The AAAI-14 Workshop program was held Sunday and Monday, July 27-28, 2014, at the Québec City Convention Centre in Québec, Canada. The AAAI-14 workshop program included 15 workshops covering a wide range of topics in artificial intelligence. The titles of the workshops were Artificial Intelligence and Robotics;Artificial Intelligence Applied to Assistive Technologies and Smart Environments;Cognitive computing for Augmented Human Intelligence;Computer Poker and Imperfect Information;Discovery Informatics;Incentives and Trust in Electronic Communities;Intelligent Cinematography and Editing;Machine Learning for Interactive Systems: Bridging the Gap Between Perception, Action, and Communication;Modern Artificial Intelligence for Health Analytics;Multiagent Interaction Without Prior Coordination;Multidisciplinary Workshop on Advances in Preference Handling;Semantic Cities - Beyond Open data to Models, Standards, and Reasoning;Sequential Decision Making with Big data;Statistical Relational AI;and the World Wide Web and Public Health Intelligence. This article presents short summaries of those events. © 2015, Association for the Advancement of Artificial Intelligence. All rights reserved.

关键词： Decision making

来源：评论

学校读者我要写书评

暂无评论

A Comparative Study of Autonomous Learning Outlier Detection Methods Applied to Fault Detection

A Comparative Study of Autonomous Learning Outlier Detection...

引用

IEEE International Conference on Fuzzy Systems

作者： Clauber Gomes Bezerra Bruno Sielly Jales Costa Luiz Affonso Guedes Plamen Parvanov Angelov Campus EaD Federal Institute of Rio Grande do Norte - IFRN Natal Brazil Campus Natal - Zona Norte Federal Institute of Rio Grande do Norte - IFRN Natal Brazil Department of Computer Engineering and Automation Federal University of Rio Grande do Norte - UFRN Lancaster University Data Science Group School of Computing and Communications Lancaster LA1 4WA United Kingdom Chair of Excellence Carlos III University Madrid Spain

ISBN: (纸本)9781467374293

Outlier detection is a problem that has been largely studied in the past few years due to its great applicability in real world problems (e.g. financial, social, climate, security). Fault detection in industrial processes is one of these problems. In that context, several methods have been proposed in literature to address fault detection. In this paper we propose a comparative analysis of three recently introduced outlier detection methods: RDE, RDE with Forgetting and TEDA. Such methods were applied to the data set provided in DAMADICS benchmark, a very well-known real data tool for fault detection applications. The results, however, can be extended to similar problems of the area. Therewith, in this work we compare the main features of each method as well as the results obtained with them.

关键词： Comparative Study Autonomous Learning Outlier Detection Methods Applied Fault Detection

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：