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Using Cost-Sensitive Ranking Loss to Improve Distant Supervised Relation Extraction

Using Cost-Sensitive Ranking Loss to Improve Distant Supervi...

第十六届全国计算语言学学术会议暨第五届基于自然标注大数据的自然语言处理国际学术研讨会

作者： Daojian Zeng Junxin Zeng Yuan Dai Hunan Provincial Key Laboratory of Intelligent Processing of Big Data on Transportation School of Computer and Communication EngineeringChangsha University of Science and TechnologyChangsha 410004P.R.China

ISBN: (纸本)9783319690049

Recently,many researchers have concentrated on using neu-ral networks to learn features for Distant Supervised Relation Extraction(DSRE).However,these approaches generally employ a softmax classi-fier with cross-entropy loss,and bring the noise of artificial class NA into classification ***,the class imbalance problem is serious in the automatically labeled data,and results in poor classification rates on minor classes in traditional *** this work,we exploit cost-sensitive ranking loss to improve *** first uses a Piecewise Convolutional Neural Network(PCNN)to embed the semantics of *** the features are fed into a classifier which takes into account both the ranking loss and ***-periments show that our method is effective and performs better than state-of-the-art methods.

关键词： Classifiers Neural network Semantics Noise Balance impairment Taxonomy embedding

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Search for time-dependent CP violation in D0→K+K− and D0→π+π− decays

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Physical Review D 2021年第7期104卷 072010-072010页

作者： R. Aaij C. Abellán Beteta T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. A. Aidala S. Aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato Y. Amhis L. An L. Anderlini A. Andreianov M. Andreotti F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back S. Baker P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista Leite R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella A. Bertolin C. Betancourt F. Betti Ia. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker S. Bifani P. Billoir M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice L. Calero Diaz S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes A. Camboni P. Campana A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti L. Carus K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli A. J. Chadwick M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier J. L. Cobbledick V. Coco J. A. B. Coelho J Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France University of Michigan Ann Arbor USA (associated with Syracuse University Syracuse New York USA) INFN Sezione di Milano Milano Italy University of Cincinnati Cincinnati Ohio USA Fakultät Physik Technische Universität Dortmund Dortmund Germany European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom ICCUB Universitat de Barcelona Barcelona Spain Department of Physics and Astronomy University of Manchester Manchester United Kingdom Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Cavendish Laboratory University of Cambridge Cambridge United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France INFN Sezione di Firenze Firenze Italy INFN Sezione di Ferrara Ferrara Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Department of Physics University of Warwick Coventry United Kingdom Imperial College London Lond

A search for time-dependent violation of the charge-parity symmetry in D0→K+K− and D0→π+π− decays is performed at the LHCb experiment using proton-proton collision data recorded from 2015 to 2018 at a center-of-mass energy of 13 TeV, corresponding to an integrated luminosity of 6 fb−1. The D0 meson is required to originate from a D*(2010)+→D0π+ decay, such that its flavor at production is identified by the charge of the accompanying pion. The slope of the time-dependent asymmetry of the decay rates of D0 and D¯0 mesons into the final states under consideration is measured to be ΔYK+K−=(−2.3±1.5±0.3)×10−4, ΔYπ+π−=(−4.0±2.8±0.4)×10−4, where the first uncertainties are statistical and the second are systematic. These results are compatible with the conservation of the charge-parity symmetry at the level of 2 standard deviations and improve the precision by nearly a factor of 2.

关键词： Hadronic decays Particle decays Quark mixing Charmed mesons CP symmetry

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Measurement of CP asymmetry in D0→KS0KS0 decays

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Physical Review D 2021年第3期104卷 L031102-L031102页

A measurement of the CP asymmetry in D0→KS0KS0 decays is reported, based on a data sample of proton-proton collisions collected by the LHCb experiment from 2015 to 2018, corresponding to an integrated luminosity of 6 fb−1. The flavor of the D0 candidate is determined using the charge of the D*± meson, from which the decay is required to originate. The D0→K+K− decay is used as a calibration channel. The time-integrated CP asymmetry for the D0→KS0KS0 mode is measured to be ACP(D0→KS0KS0)=(−3.1±1.2±0.4±0.2), where the first uncertainty is statistical, the second is systematic, and the third is due to the uncertainty on the CP asymmetry of the calibration channel. This is the most precise determination of this quantity to date.

关键词： Charmed mesons CP violation

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Precise measurement of the fs/fd ratio of fragmentation fractions and of Bs0 decay branching fractions

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Physical Review D 2021年第3期104卷 032005-032005页

作者： R. Aaij C. Abellán Beteta T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. A. Aidala S. Aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato Y. Amhis L. An L. Anderlini A. Andreianov M. Andreotti F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back S. Baker P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista Leite R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella A. Bertolin C. Betancourt F. Betti Ia. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker S. Bifani P. Billoir M. Birch F. C. R. Bishop A. Bitadze A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice L. Calero Diaz S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes A. Camboni P. Campana A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti L. Carus K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli A. J. Chadwick M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier J. L. Cobbledick V. Coco J. A. B. Coelho J Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France University of Michigan Ann Arbor Michigan USA (associated with Syracuse University Syracuse New York USA) INFN Sezione di Milano Milano Italy University of Cincinnati Cincinnati Ohio USA Fakultät Physik Technische Universität Dortmund Dortmund Germany European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom ICCUB Universitat de Barcelona Barcelona Spain Department of Physics and Astronomy University of Manchester Manchester United Kingdom Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Cavendish Laboratory University of Cambridge Cambridge United Kingdom Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France INFN Sezione di Firenze Firenze Italy INFN Sezione di Ferrara Ferrara Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Laboratoire Leprince-Ringuet CNRS/IN2P3 Ecole Polytechnique Institut Polytechnique de Paris Palaiseau France Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Department of Physics University of Warwick Coventry United Kingdom Imperial College Lo

The ratio of the Bs0 and B0 fragmentation fractions, fs/fd, in proton-proton collisions at the LHC, is obtained as a function of B-meson transverse momentum and collision center-of-mass energy from the combined analysis of different B-decay channels measured by the LHCb experiment. The results are described by a linear function of the meson transverse momentum or with a function inspired by Tsallis statistics. Precise measurements of the branching fractions of the Bs0→J/ψϕ and Bs0→Ds−π+ decays are performed, reducing their uncertainty by about a factor of 2 with respect to previous world averages. Numerous Bs0 decay branching fractions, measured at the LHCb experiment, are also updated using the new values of fs/fd and branching fractions of normalization channels. These results reduce a major source of systematic uncertainty in several searches for new physics performed through measurements of Bs0 branching fractions.

关键词： Branching fraction Fragmentation into hadrons

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Observation of a new Ξb0 state

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Physical Review D 2021年第1期103卷 012004-012004页

作者： R. Aaij C. Abellán Beteta T. Ackernley B. Adeva M. Adinolfi H. Afsharnia C. A. Aidala S. Aiola Z. Ajaltouni S. Akar J. Albrecht F. Alessio M. Alexander A. Alfonso Albero Z. Aliouche G. Alkhazov P. Alvarez Cartelle S. Amato Y. Amhis L. An L. Anderlini A. Andreianov M. Andreotti F. Archilli A. Artamonov M. Artuso K. Arzymatov E. Aslanides M. Atzeni B. Audurier S. Bachmann M. Bachmayer J. J. Back S. Baker P. Baladron Rodriguez V. Balagura W. Baldini J. Baptista Leite R. J. Barlow S. Barsuk W. Barter M. Bartolini F. Baryshnikov J. M. Basels G. Bassi B. Batsukh A. Battig A. Bay M. Becker F. Bedeschi I. Bediaga A. Beiter V. Belavin S. Belin V. Bellee K. Belous I. Belov I. Belyaev G. Bencivenni E. Ben-Haim A. Berezhnoy R. Bernet D. Berninghoff H. C. Bernstein C. Bertella E. Bertholet A. Bertolin C. Betancourt F. Betti M. O. Bettler Ia. Bezshyiko S. Bhasin J. Bhom L. Bian M. S. Bieker S. Bifani P. Billoir M. Birch F. C. R. Bishop A. Bizzeti M. Bjørn M. P. Blago T. Blake F. Blanc S. Blusk D. Bobulska J. A. Boelhauve O. Boente Garcia T. Boettcher A. Boldyrev A. Bondar N. Bondar S. Borghi M. Borisyak M. Borsato J. T. Borsuk S. A. Bouchiba T. J. V. Bowcock A. Boyer C. Bozzi M. J. Bradley S. Braun A. Brea Rodriguez M. Brodski J. Brodzicka A. Brossa Gonzalo D. Brundu A. Buonaura C. Burr A. Bursche A. Butkevich J. S. Butter J. Buytaert W. Byczynski S. Cadeddu H. Cai R. Calabrese L. Calefice L. Calero Diaz S. Cali R. Calladine M. Calvi M. Calvo Gomez P. Camargo Magalhaes A. Camboni P. Campana D. H. Campora Perez A. F. Campoverde Quezada S. Capelli L. Capriotti A. Carbone G. Carboni R. Cardinale A. Cardini I. Carli P. Carniti K. Carvalho Akiba A. Casais Vidal G. Casse M. Cattaneo G. Cavallero S. Celani J. Cerasoli A. J. Chadwick M. G. Chapman M. Charles Ph. Charpentier G. Chatzikonstantinidis C. A. Chavez Barajas M. Chefdeville C. Chen S. Chen A. Chernov S.-G. Chitic V. Chobanova S. Cholak M. Chrzaszcz A. Chubykin V. Chulikov P. Ciambrone M. F. Cicala X. Cid Vidal G. Ciezarek P. E. L. Clarke M. Clemencic H. V. Cliff J. Closier J. Nikhef National Institute for Subatomic Physics Amsterdam Netherlands Physik-Institut Universität Zürich Zürich Switzerland Oliver Lodge Laboratory University of Liverpool Liverpool United Kingdom Instituto Galego de Física de Altas Enerxías (IGFAE) Universidade de Santiago de Compostela Santiago de Compostela Spain H.H. Wills Physics Laboratory University of Bristol Bristol United Kingdom Université Clermont Auvergne CNRS/IN2P3 LPC Clermont-Ferrand France University of Michigan Ann Arbor USA (associated with Syracuse University Syracuse New York USA) INFN Sezione di Milano Milano Italy University of Cincinnati Cincinnati Ohio USA Fakultät Physik Technische Universität Dortmund Dortmund Germany European Organization for Nuclear Research (CERN) Geneva Switzerland School of Physics and Astronomy University of Glasgow Glasgow United Kingdom ICCUB Universitat de Barcelona Barcelona Spain Department of Physics and Astronomy University of Manchester Manchester United Kingdom Petersburg Nuclear Physics Institute NRC Kurchatov Institute (PNPI NRC KI) Gatchina Russia Universidade Federal do Rio de Janeiro (UFRJ) Rio de Janeiro Brazil Université Paris-Saclay CNRS/IN2P3 IJCLab Orsay France INFN Sezione di Firenze Firenze Italy INFN Sezione di Ferrara Ferrara Italy Physikalisches Institut Ruprecht-Karls-Universität Heidelberg Heidelberg Germany Institute for High Energy Physics NRC Kurchatov Institute (IHEP NRC KI) Protvino Russia Protvino Russia Syracuse University Syracuse New York USA Yandex School of Data Analysis Moscow Russia Aix Marseille Univ CNRS/IN2P3 CPPM Marseille France Institute of Physics Ecole Polytechnique Fédérale de Lausanne (EPFL) Lausanne Switzerland Department of Physics University of Warwick Coventry United Kingdom Imperial College London London United Kingdom Centro Brasileiro de Pesquisas Físicas (CBPF) Rio de Janeiro Brazil INFN Sezione di Genova Genova Italy National University of Science and Technology “MISIS” Mosco

Using a proton-proton collision data sample collected by the LHCb experiment, corresponding to an integrated luminosity of 8.5 fb−1, the observation of a new excited Ξb0 resonance decaying to the Ξb−π+ final state is presented. The state, referred to as Ξb(6227)0, has a measured mass and natural width of m(Ξb(6227)0)=6227.1−1.5+1.4±0.5 MeV and Γ(Ξb(6227)0)=18.6−4.1+5.0±1.4 MeV, where the uncertainties are statistical and systematic. The production rate of the Ξb(6227)0 state relative to that of the Ξb− baryon in the kinematic region 2<η<5 and pT<30 GeV is measured to be fΞb(6227)0fΞb−B(Ξb(6227)0→Ξb−π+)=0.045±0.008±0.004, where B(Ξb(6227)0→Ξb−π+) is the branching fraction of the decay, and fΞb(6227)0 and fΞb− represent fragmentation fractions. Improved measurements of the mass and natural width of the previously observed Ξb(6227)− state, along with the mass of the Ξb− baryon, are also reported. Both measurements are significantly more precise than, and consistent with, previously reported values.

关键词： Bottom baryons

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A gene expression map of shoot domains reveals new regulatory mechanisms

A gene expression map of shoot domains reveals new regulator...

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中国植物学会第十六次全国会员代表大会暨85周年学术年会

作者： Caihuan Tian Ying Wang Haopeng Yu Jun He Jin Wang Bihai Shi Qingwei Du Nicholas J.Provart Elliot M.Meyerowitz Yuling Jiao State Key Laboratory of Plant Genomics Institute of Genetics and Developmental BiologyChinese Academy of Sciences College of Life Sciences University of Chinese Academy of Sciences West China Biomedical Big Data Center West China Hospital/West China School of Medicineand Medical Big Data CenterSichuan University Horticultural Plant Biology and Metabolomics Center Institute of Science and TechnologyFujian Agricultural and Forestry University Zhongshan School of Medicine Sun Yat-sen University Laboratoire Reproduction et Developpement des Plantes Univ LyonENS de Lyon Department of Cell and Systems Biology Centre for the Analysis of Genome Evolution and FunctionUniversity of Toronto Howard Hughes Medical Institute and Division of Biology and Biological Engineering California Institute of Technology

Gene regulatory networks control development via cell type-specific gene *** seed plants,self-renewing stem cells located in the shoot apical meristem(SAM)produce leaves from the SAM peripheral *** develop polarity patterns following initiation to form a planar *** we provide a comparison of translating RNAs among SAM and leaf *** used RNA sequencing to quantify gene

关键词： A gene expression map of shoot domains reveals new regulatory mechanisms

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An evolutionary algorithm based ontology matching system

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Journal of Information Hiding and Multimedia Signal Processing 2017年第3期8卷 551-556页

作者： Xue, Xingsi Tang, Zhengyi College of Information Science and Engineering Fujian Provincial Key Laboratory of Big Data Mining and Applications Fujian University of Technology No3 Xueyuan Road University Town Minhou Fuzhou CityFujian Province350118 China

Due to the high heterogeneity of ontologies, a combination of many methods is necessary to discover correctly the semantic correspondences between their elements. An ontology matching system can be seen as a collection of several matching components, which implements a specific method dealing with a specific heterogeneity type like the ter- minological, structural and semantic matchers. In this paper, a novel ontology matching system architecture is proposed and the details of its kernel model are presented, i.e. matching and mapping extraction module, where we construct a new optimal model for the ontology matching and mapping extraction problem and design a problem specific Evolutionary Algorithm (EA) for it. The experimental results show that the mean recall and precision of our approach is generally high, and the mean f-measure of the align- ments obtained by our approach outperform all other state of the art matching systems. © 2017.

关键词： Extraction

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Social contagions with communication channel alternation on multiplex networks

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Physical Review E 2018年第6期98卷 062320-062320页

作者： Wei Wang Ming Tang H. Eugene Stanley Lidia A. Braunstein Cybersecurity Research Institute Sichuan University Chengdu 610065 China Big Data Research Center University of Electronic Science and Technology of China Chengdu 610054 China School of Information Science and Technology East China Normal University Shanghai 200241 China Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China Center for Polymer Studies and Department of Physics Boston University Boston Massachusetts 02215 USA Instituto de Investigaciones Físicas de Mar del Plata (IFIMAR)-Departamento de Física Facultad de Ciencias Exactas y Naturales Universidad Nacional de Mar del Plata-CONICET Funes 3350 (7600) Mar del Plata Argentina

Internet communication channels, e.g., Facebook, Twitter, and email, are multiplex networks that facilitate interaction and information-sharing among individuals. During brief time periods users often use a single communication channel, but then communication channel alteration (CCA) occurs. This means that we must refine our understanding of the dynamics of social contagions. We propose a non-Markovian behavior spreading model in multiplex networks that takes into account the CCA mechanism, and we develop a generalized edge-based compartmental method to describe the spreading dynamics. Through extensive numerical simulations and theoretical analyses we find that the time delays induced by CCA slow the behavior spreading but do not affect the final adoption size. We also find that the CCA suppresses behavior spreading. On two coupled random regular networks, the adoption size exhibits hybrid growth, i.e., it grows first continuously and then discontinuously with the information transmission probability. CCA in Erdős-Rényi–Scale-Free (ER-SF) multiplex networks in which two subnetworks are ER and SF introduces a crossover from continuous to hybrid growth in adoption size versus information transmission probability. Our results extend our understanding of the role of CCA in spreading dynamics and may elicit further research.

关键词： Network phase transitions Network structure Spreading Multilayer & multiplex networks Epidemic spreading

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Publisher Correction: Equivalence and its invalidation between non-Markovian and Markovian spreading dynamics on complex networks

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Nature communications 2019年第1期10卷 4677页

作者： Mi Feng Shi-Min Cai Ming Tang Ying-Cheng Lai School of Mathematical Sciences Shanghai Key Laboratory of PMMP East China Normal University Shanghai 200241 China. Web Sciences Center University of Electronic Science and Technology of China Chengdu 611731 China. Big Data Research Center University of Electronic Science and Technology of China Chengdu 611731 China. School of Mathematical Sciences Shanghai Key Laboratory of PMMP East China Normal University Shanghai 200241 China. tangminghan007@***. Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University Shanghai 200241 China. tangminghan007@***. School of Electrical Computer and Energy Engineering Arizona State University Tempe AZ 85287 USA.

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

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Using deep learning to recognize biomedical entities

Using deep learning to recognize biomedical entities

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International Conference on Intelligent System and Knowledge Engineering, ISKE

作者： Xuemin Yang Zhifei Zhang Ronggen Yang Daoyu Huang Geng Yang Lejun Gong Jiangsu Key Laboratory of Big Data Security &Intelligent Processing Nanjing University of Posts and Telecommunications Nanjing China Faculty Intelligent Science and Control Engineering Jinling Institute of Technology Nanjing China

With the rapid growth of the high-throughput biological technology, it brings biomedical big omics' data containing literature and annotated data. Especially, a wealth of relevant information exists in various types of biomedical literature. Text mining has emerged as a potential solution to achieve knowledge for bridging between the free text and structured representation of biomedical information. In this work, we used deep learning to recognize biomedical entities. We obtained 84.0% precision, 69.5% recall, and 76.1% F-score aiming at the GENIA corpus, and obtained 91.3% precision, 91.1% recall, and 91.2% F-score aiming at the BioCreAtIvE II Gene Mention corpus. Experimental results show that our proposed approach is promising for developing biomedical text mining technology in biomedical entity recognition.

关键词： Machine learning Neural networks Text mining Dictionaries Distributed databases Biological system modeling Telecommunications

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