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arXiv 2018年

作者： Saeed, Taqwa Skitsas, Constantinos Kouzapas, Dimitrios Lestas, Marios Soteriou, Vassos Philippou, Anna Abadal, Sergi Liaskos, Christos Petrou, Loukas Georgiou, Julius Pitsillides, Andreas Department of Electrical Engineering Frederick University Cyprus Nicosia Cyprus Department of Computer Science University of Cyprus Nicosia Cyprus Dept. of Electrical Eng. Computer Eng. and Informatics Cyprus University of Technology Limassol Cyprus Department of Computer Architecture Universitat Politècnica de Catalunya Barcelona Spain Institute of Computer Science Foundation of Research and Technology Hellas Heraklion Greece Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

HyperSurfaces are a merge of structurally reconfigurable metasurfaces whose electromagnetic properties can be changed via a software interface, using an embedded miniaturized network of controllers, thus enabling novel capabilities in wireless communications. Resource constraints associated with the development of a hardware testbed of this breakthrough technology necessitate network controller architectures different from traditional regular Network-on-Chip architectures. The Manhattan-like topology chosen to realize the controller network in the testbed under development is irregular, with restricted local path selection options, operating in an asynchronous fashion. These characteristics render traditional fault-tolerant routing mechanisms inadequate. In this paper, we present work in progress towards the development of fault-tolerant routing mechanisms for the chosen architecture. We present two XY-based approaches which have been developed aiming to offer reliable data delivery in the presence of faults. The first approach aims to avoid loops while the second one attempts to maximize the success delivery probabilities. Their effectiveness is demonstrated via simulations conducted on a custom developed simulator. Copyright © 2018, The Authors. All rights reserved.

关键词： Network routing

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Fault Adaptive Routing in Metasurface Controller Networks

Fault Adaptive Routing in Metasurface Controller Networks

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International Workshop on Network on Chip Architectures, NoCArc

作者： Taqwa Saeed Constantinos Skitsas Dimitrios Kouzapas Marios Lestas Vassos Soteriou Anna Philippou Sergi Abadal Christos Liaskos Loukas Petrou Julius Georgiou Andreas Pitsillides Department of Computer Science University of Cyprus Nicosia Cyprus Department of Electrical Engineering Frederick University Cyprus Nicosia Cyprus Dept. of Electrical Eng. Computer Eng. and Informatics Cyprus University of Technology Limassol Cyprus Department of Computer Architecture Universitat Politècnica de Catalunya Barcelona Spain Institute of Computer Science Foundation of Research and Technology Hellas Heraklion Greece Department of Electrical and Computer Engineering University of Cyprus Nicosia Cyprus

关键词： Routing Topology System recovery Pins Network topology Logic gates Fault tolerance

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OS12.7.A Characterization of intra-tumoral heterogeneity and differential immune activation during malignant progression of meningiomas on single cell level

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Neuro-Oncology 2021年第SUPPLEMENT_2期23卷 ii15-ii16页

作者： Blume, C Dogan, H Schweizer, L Wick, W Weller, M Mann, M Kalamarides, M von Deimling, A Schlesner, M Sahm, F CCU Neuropathology German Cancer Research Centre (DKFZ) Heidelberg Germany Dept. of Neuropathology University Hospital Heidelberg Heidelberg Germany Department of Proteomics and Signal Transduction Max Planck Institute of Biochemistry Martinsried Germany German Cancer Research Centre (DKFZ) Heidelberg Germany Department of Neurology and Neurooncology Program National Center for Tumor Diseases Heidelberg University Hospital Heidelberg Germany Department of Neurology Clinical Neuroscience Center University Hospital and University of Zürich Zürich Switzerland NNF Center for Protein Research Faculty of Health Sciences University of Copenhagen Copenhagen Denmark Sorbonne Université and Department of Neurosurgery Pitié Salpêtrière Hospital Paris France Biomedical Informatics Data Mining and Data Analytics Faculty of Applied Computer Science and Medical Faculty University of Augsburg Augsburg Germany

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Measurement of the tt¯ cross section and its ratio to the Z production cross section using pp collisions at s=13.6 TeV with the ATLAS detector

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2024年 848卷

作者： Aad, G. Abbott, B. Abbott, D.C. Abdinov, O. Abud, A. Abed Abeling, K. Abhayasinghe, D.K. Abidi, S.H. AbouZeid, O.S. Abraham, N.L. Abramowicz, H. Abreu, H. Abulaiti, Y. Acharya, B.S. Achkar, B. Adachi, S. Adam, L. Bourdarios, C. Adam Adamczyk, L. Adamek, L. Adelman, J. Adersberger, M. Adiguzel, A. Adorni, S. Adye, T. Affolder, A.A. Afik, Y. Agapopoulou, C. Agaras, M.N. Aggarwal, A. Agheorghiesei, C. Aguilar-Saavedra, J.A. Ahmadov, F. Ahmed, W.S. Ai, X. Aielli, G. Akatsuka, S. Åkesson, T.P.A. Akilli, E. Akimov, A.V. Al Khoury, K. Alberghi, G.L. Albert, J. Verzini, M. J. Alconada Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexandre, D. Alexopoulos, T. Alfonsi, A. Alhroob, M. Ali, B. Alimonti, G. Alison, J. Alkire, S.P. Allaire, C. Allbrooke, B.M.M. Allen, B.W. Allport, P.P. Aloisio, A. Alonso, A. Alonso, F. Alpigiani, C. Alshehri, A.A. Estevez, M. Alvarez Piqueras, D. Álvarez Alviggi, M.G. Coutinho, Y. Amaral Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Dos Santos, S. P. Amor Amoroso, S. Amrouche, C.S. An, F. Anastopoulos, C. Andari, N. Andeen, T. Anders, C.F. Anders, J.K. Andreazza, A. Andrei, V. Anelli, C.R. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antonelli, M. Antrim, D.J.A. Anulli, F. Aoki, M. Pozo, J. A. Aparisi Bella, L. Aperio Arabidze, G. Araque, J.P. Ferraz, V. Araujo Pereira, R. Araujo Arcangeletti, C. Arce, A.T.H. Arduh, F.A. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Armbruster, A.J. Armitage, L.J. Armstrong, A. Arnaez, O. Arnold, H. Artamonov, A. Artoni, G. Artz, S. Asai, S. Asbah, N. Asimakopoulou, E.M. Asquith, L. Assamagan, K. Astalos, R. Atkin, R.J. Atkinson, M. Atlay, N.B. Atmani, H. Augsten, K. Avolio, G. Avramidou, R. Ayoub, M.K. Azoulay, A.M. Azuelos, G. Baca, M.J. Bachacou, H. Bachas, K. Backes, M. Backman, F. Bagnaia, P. Bahmani, M. Bahrasemani, H. Bailey, A.J. Bailey, V.R. Baines, J.T. Bajic, M. Bakalis, C. Baker, O.K. Bakker, P.J. Gupta, D. Bakshi Balaji, S. Baldin, E.M. Balek, P. Balli, F. Balunas, W.K. Balz, J. Banas, E. Bandyopadhyay CPPM Aix-Marseille Université CNRS/IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States Department of Physics University of Massachusetts Amherst MA United States Institute of Physics Azerbaijan Academy of Sciences Baku Azerbaijan INFN Sezione di Pavia Italy Dipartimento di Fisica Università di Pavia Pavia Italy II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Department of Physics University of Toronto Toronto ON Canada Niels Bohr Institute University of Copenhagen Copenhagen Denmark Department of Physics and Astronomy University of Sussex Brighton United Kingdom Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne IL United States CERN Geneva Switzerland INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King's College London London United Kingdom International Center for Elementary Particle Physics Department of Physics University of Tokyo Tokyo Japan Institut für Physik Universität Mainz Mainz Germany IJCLab Université Paris-Sud CNRS/IN2P3 Université Paris-Saclay Orsay France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics Northern Illinois University DeKalb IL United States Fakultät für Physik Ludwig-Maximilians-Universität München München Germany Department of Physics Bogazici University Istanbul Turkey Istanbul University Dept. of Physics Istanbul Turkey Bruno Kessler Foundation Trento Italy Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laborato

The inclusive top-quark-pair production cross section σtt¯ and its ratio to the Z-boson production cross section have been measured in proton–proton collisions at s=13.6 TeV, using 29 fb−1 of data collected in ...

The inclusive top-quark-pair production cross section σ_tt¯ and its ratio to the Z-boson production cross section have been measured in proton–proton collisions at s=13.6 TeV, using 29 fb⁻¹ of data collected in 2022 with the ATLAS experiment at the Large Hadron Collider. Using events with an opposite-charge electron-muon pair and b-tagged jets, and assuming Standard Model decays, the top-quark-pair production cross section is measured to be σ_tt¯=850±3(stat.)±18(syst.)±20(lumi.) pb. The ratio of the tt¯ and the Z-boson production cross sections is also measured, where the Z-boson contribution is determined for inclusive e⁺e⁻ and μ⁺μ⁻ events in a fiducial phase space. The relative uncertainty on the ratio is reduced compared to the tt¯ cross section, thanks to the cancellation of several systematic uncertainties. The result for the ratio, R_tt¯/Z=1.145±0.003(stat.)±0.021(syst.)±0.002(lumi.) is consistent with the Standard Model prediction using the PDF4LHC21 PDF set. © 2023 The Author(s)

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Evaluation of sensors’ precision in a low cost e-health monitoring system 8

Evaluation of sensors’ precision in a low cost e-health mon...

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8th International Conference on Information and Communication Technologies in Agriculture, Food and Environment, HAICTA 2017

作者： Petrellis, Nikos Birbas, Michael Gioulekas, Fotios Department of Computer Science and Engineering Technology Educational Institute of Thessaly Greece Electrical Engineering and Computer Technology Dept. University of Patras Greece Analogies S.A. Greece Sub-directorate of Informatics University General Hospital of Larissa Larissa Greece

In this paper, a low cost e-health platform is evaluated concerning the precision of the employed sensors. The sensors used by the developed e-health platform are not medically certified but are compared against medically certified ones. The developed platform exhibits enhanced key characteristics to cover a broad range of medical scenarios in a reliable and flexible way. A low-cost Sensor Controller capable of performing both simple medical tests and more advanced ones communicates with a Gateway and a tablet or smart phone providing instructions to the patient. The employed protocol used for the communication between the Sensor Controller and the Gateway, supports a variety of sensors with different sampling profiles. The platform exhibits high portability due to the power saving modes that have been employed. However, the sensors’ accuracy is an important issue that is investigated in this paper in order to highlight the medical cases where the (low-cost) developed e-health platform can be used in a fairly reliable way. Such a platform would be especially useful for the enhancement of the quality of life of residents in distant or isolated rural areas. Moreover, it would be possible to use part of this platform for the continuous monitoring of livestock (e.g., excluding the tablet/phone). Copyright © 2017 for this paper by its author

关键词： Smartphones

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Beyond Low Earth Orbit: Biological Research, Artificial Intelligence, and Self-Driving Labs

arXiv

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arXiv 2021年

作者： Sanders, Lauren M. Yang, Jason H. Scott, Ryan T. Qutub, Amina Ann Martin, Hector Garcia Berrios, Daniel C. Hastings, Jaden J.A. Rask, Jon Mackintosh, Graham Hoarfrost, Adrienne L. Chalk, Stuart Kalantari, John Khezeli, Kia Antonsen, Erik L. Babdor, Joel Barker, Richard Baranzini, Sergio E. Beheshti, Afshin Delgado-Aparicio, Guillermo M. Glicksberg, Benjamin S. Greene, Casey S. Haendel, Melissa Hamid, Arif A. Heller, Philip Jamieson, Daniel Jarvis, Katelyn J. Komarova, Svetlana V. Komorowski, Matthieu Kothiyal, Prachi Mahabal, Ashish Manor, Uri Mason, Christopher E. Matar, Mona Mias, George I. Miller, Jack Myers, Jerry G. Nelson, Charlotte Oribello, Jonathan Park, Seung-Min Parsons-Wingerter, Patricia Prabhu, R.K. Reynolds, Robert J. Saravia-Butler, Amanda Saria, Suchi Sawyer, Aenor Singh, Nitin Kumar Soboczenski, Frank Snyder, Michael Soman, Karthik Theriot, Corey A. van Valen, David Venkateswaran, Kasthuri Warren, Liz Worthey, Liz Zitnik, Marinka Costes, Sylvain V. Blue Marble Space Institute of Science Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Center for Emerging and Re-Emerging Pathogens Department of Microbiology Biochemistry and Molecular Genetics Rutgers New Jersey Medical School NewarkNJ07103 United States KBR Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States AI MATRIX Consortium Department of Biomedical Engineering University of Texas San Antonio and UT Health Sciences San AntonioTX78249 United States Biological Systems and Engineering Division Lawrence Berkeley National Lab. BerkeleyCA94608 United States DOE Agile BioFoundry EmeryvilleCA94608 United States Joint BioEnergy Institute EmeryvilleCA94608 United States Department of Physiology and Biophysics Weill Cornell Medicine New YorkNY10065 United States Office of the Center Director NASA Ames Research Center Moffett Field CA94035 United States Bay Area Environmental Research Institute NASA Ames Research Center Moffett Field CA94035 United States Space Biosciences Division NASA Ames Research Center Moffett Field CA94035 United States Department of Chemistry University of North Florida JacksonvilleFL32224 United States Center for Individualized Medicine Department of Surgery Department of Quantitative Health Sciences Mayo Clinic RochesterMN55905 United States Department of Emergency Medicine Center for Space Medicine Baylor College of Medicine HoustonTX77030 United States Department of Microbiology and Immunology Department of Otolaryngology Head and Neck Surgery University of California San Francisco San FranciscoCA94143 United States The Gilroy AstroBiology Research Group The University of Wisconsin - Madison MadisonWI53706 United States Weill Institute for Neurosciences Department of Neurology University of California San Francisco San FranciscoCA94158 United States Data Science Analytics Georgia Institute of Technology Lima15024

Space biology research aims to understand fundamental effects of spaceflight on organisms, develop foundational knowledge to support deep space exploration, and ultimately bioengineer spacecraft and habitats to stabilize the ecosystem of plants, crops, microbes, animals, and humans for sustained multi-planetary life. To advance these aims, the field leverages experiments, platforms, data, and model organisms from both spaceborne and ground-analog studies. As research is extended beyond low Earth orbit, experiments and platforms must be maximally autonomous, light, agile, and intelligent to expedite knowledge discovery. Here we present a summary of recommendations from a workshop organized by the National Aeronautics and Space Administration on artificial intelligence, machine learning, and modeling applications which offer key solutions toward these space biology challenges. In the next decade, the synthesis of artificial intelligence into the field of space biology will deepen the biological understanding of spaceflight effects, facilitate predictive modeling and analytics, support maximally autonomous and reproducible experiments, and efficiently manage spaceborne data and metadata, all with the goal to enable life to thrive in deep space. © 2021, CC BY.

关键词： Predictive analytics

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Search for the Zγ decay mode of new high-mass resonances in pp collisions at s=13 TeV with the ATLAS detector

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2024年 848卷

作者： Aad, G. Abbott, B. Abbott, D.C. Abed Abud, A. Abeling, K. Abhayasinghe, D.K. Abidi, S.H. Aboulhorma, A. Abramowicz, H. Abreu, H. Abulaiti, Y. Abusleme Hoffman, A.C. Acharya, B.S. Achkar, B. Adam, L. Adam Bourdarios, C. Adamczyk, L. Adamek, L. Addepalli, S.V. Adelman, J. Adiguzel, A. Adorni, S. Adye, T. Affolder, A.A. Afik, Y. Agapopoulou, C. Agaras, M.N. Agarwala, J. Aggarwal, A. Agheorghiesei, C. Aguilar-Saavedra, J.A. Ahmad, A. Ahmadov, F. Ahmed, W.S. Ai, X. Aielli, G. Aizenberg, I. Akatsuka, S. Akbiyik, M. Åkesson, T.P.A. Akimov, A.V. Al Khoury, K. Alberghi, G.L. Albert, J. Albicocco, P. Alconada Verzini, M.J. Alderweireldt, S. Aleksa, M. Aleksandrov, I.N. Alexa, C. Alexopoulos, T. Alfonsi, A. Alfonsi, F. Alhroob, M. Ali, B. Ali, S. Aliev, M. Alimonti, G. Allaire, C. Allbrooke, B.M.M. Allport, P.P. Aloisio, A. Alonso, F. Alpigiani, C. Alunno Camelia, E. Alvarez Estevez, M. Alviggi, M.G. Amaral Coutinho, Y. Ambler, A. Ambroz, L. Amelung, C. Amidei, D. Amor Dos Santos, S.P. Amoroso, S. Amos, K.R. Amrouche, C.S. Ananiev, V. Anastopoulos, C. Andari, N. Andeen, T. Anders, J.K. Andrean, S.Y. Andreazza, A. Anelli, C.R. Angelidakis, S. Angerami, A. Anisenkov, A.V. Annovi, A. Antel, C. Anthony, M.T. Antipov, E. Antonelli, M. Antrim, D.J.A. Anulli, F. Aoki, M. Aparisi Pozo, J.A. Aparo, M.A. Aperio Bella, L. Aranzabal, N. Araujo Ferraz, V. Arcangeletti, C. Arce, A.T.H. Arena, E. Arguin, J.-F. Argyropoulos, S. Arling, J.-H. Armbruster, A.J. Armstrong, A. Arnaez, O. Arnold, H. Arrubarrena Tame, Z.P. Artoni, G. Asada, H. Asai, K. Asai, S. Asbah, N.A. Asimakopoulou, E.M. Asquith, L. Assahsah, J. Assamagan, K. Astalos, R. Atkin, R.J. Atkinson, M. Atlay, N.B. Atmani, H. Atmasiddha, P.A. Augsten, K. Auricchio, S. Austrup, V.A. Avner, G. Avolio, G. Ayoub, M.K. Azuelos, G. Babal, D. Bachacou, H. Bachas, K. Bachiu, A. Backman, F. Badea, A. Bagnaia, P. Bahrasemani, H. Bailey, A.J. Bailey, V.R. Baines, J.T. Bakalis, C. Baker, O.K. Bakker, P.J. Bakos, E. Bakshi Gupta, D. Balaji, S. Balasubramanian, R. Baldin, E.M. Balek, P. Ballabene CPPM Aix-Marseille Université CNRS IN2P3 Marseille France Homer L. Dodge Department of Physics and Astronomy University of Oklahoma Norman OK United States Department of Physics University of Massachusetts Amherst MA United States CERN Geneva Switzerland II. Physikalisches Institut Georg-August-Universität Göttingen Göttingen Germany Department of Physics Royal Holloway University of London Egham United Kingdom Physics Department Brookhaven National Laboratory Upton NY United States Mohammed VI Polytechnic University Ben Guerir Morocco Raymond and Beverly Sackler School of Physics and Astronomy Tel Aviv University Tel Aviv Israel Department of Physics Technion Israel Institute of Technology Haifa Israel High Energy Physics Division Argonne National Laboratory Argonne IL United States Departamento de Física Pontificia Universidad Católica de Chile Santiago Chile INFN Gruppo Collegato di Udine Sezione di Trieste Udine Italy ICTP Trieste Italy Department of Physics King’s College London London United Kingdom Institut für Physik Universität Mainz Mainz Germany LAPP Univ. Savoie Mont Blanc CNRS IN2P3 Annecy France AGH University of Science and Technology Faculty of Physics and Applied Computer Science Krakow Poland Department of Physics University of Toronto Toronto ON Canada Department of Physics Brandeis University Waltham MA United States Department of Physics Northern Illinois University DeKalb IL United States Istanbul University Dept. of Physics Istanbul Turkey Département de Physique Nucléaire et Corpusculaire Université de Genève Genève Switzerland Particle Physics Department Rutherford Appleton Laboratory Didcot United Kingdom Santa Cruz Institute for Particle Physics University of California Santa Cruz Santa Cruz CA United States IJCLab Université Paris-Saclay CNRS IN2P3 Orsay 91405 France Institut de Física d’Altes Energies (IFAE) Barcelona Institute of Science and Technology Barcelona Spain INFN Sezione di Pavia

This letter presents a search for narrow, high-mass resonances in the Zγ final state with the Z boson decaying into a pair of electrons or muons. The s=13 TeV pp collision data were recorded by the ATLAS detector at the CERN Large Hadron Collider and have an integrated luminosity of 140 fb⁻¹. The data are found to be in agreement with the Standard Model background expectation. Upper limits are set on the resonance production cross section times the decay branching ratio into Zγ. For spin-0 resonances produced via gluon–gluon fusion, the observed limits at 95% confidence level vary between 65.5 fb and 0.6 fb, while for spin-2 resonances produced via gluon–gluon fusion (or quark–antiquark initial states) limits vary between 77.4 (76.1) fb and 0.6 (0.5) fb, for the mass range from 220 GeV to 3400 GeV. © 2023 The Author(s)

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Probing the CP nature of the top–Higgs Yukawa coupling in tt¯H and tH events with H→bb¯ decays using the ATLAS detector at the LHC

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Physics Letters, Section B: Nuclear, Elementary Particle and High-Energy Physics 2024年 849卷

The CP properties of the coupling between the Higgs boson and the top quark are investigated using 139 fb−1 of proton–proton collision data recorded by the ATLAS experiment at the LHC at a centre-of-mass energy of s=...

The CP properties of the coupling between the Higgs boson and the top quark are investigated using 139 fb⁻¹ of proton–proton collision data recorded by the ATLAS experiment at the LHC at a centre-of-mass energy of s=13 TeV. The CP structure of the top quark–Higgs boson Yukawa coupling is probed in events with a Higgs boson decaying into a pair of b-quarks and produced in association with either a pair of top quarks, tt¯H, or a single top quark, tH. Events containing one or two electrons or muons are used for the measurement. Multivariate techniques are used to select regions enriched in tt¯H and tH events, where dedicated CP-sensitive observables are exploited. In an extension of the Standard Model (SM) with a CP-odd admixture in the top–Higgs Yukawa coupling, the mixing angle between CP-even and CP-odd couplings is measured to be α=11−73^∘ ^{∘+52^∘}, compatible with the SM prediction corresponding to α=0.

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Efficient sequential pattern mining with wildcards for keyphrase extraction

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Knowledge-Based Systems 2017年 115卷 27-39页

作者： Xie, Fei Wu, Xindong Zhu, Xingquan School of Computer Science and Information Engineering Hefei University of Technology Hefei 230009 China Department of Computer Science and Technology Hefei Normal University Hefei 230601 China School of Computing and Informatics University of Louisiana at Lafayette LA 70503 United States Dept. of Computer & Electrical Eng. and Computer Science Florida Atlantic Univ. Boca Raton FL 33431 United States

A keyphrase (a multi-word unit) in a document denotes one or multiple keywords capturing a main topic of the underlying document. Finding good keyphrases of a document can quickly summarize knowledge for efficient decision making and benefit domains involving intensive text information. To date, existing keyphrase extraction methods cannot be customized to each specific document, mainly because their patterns used to form paraphrases are too restrictive and may not capture flexible keyword relationships inside the text. In this paper, we propose a sequential pattern mining based document-specific keyphrase extraction method. Our key innovation is to use wildcards (or gap constraints) to help extract sequential patterns, so the flexible wildcard constraints within a pattern can capture semantic relationships between words, and the system will have full flexibility to discover different types of sequential patterns as candidates for keyphrase extraction. To achieve the goal, we regard each single document as a sequential dataset, and propose an efficient algorithm to mine sequential patterns with wildcard and one-off conditions that allows important keyphrases to be captured during the mining process. For each extracted keyphrase candidate, we use some statistical pattern features to characterize it, and further collect all keyphrases from the document to form a training set. A supervised learning classifier is trained to identify keyphrases from a test document. Because our pattern mining and pattern characterization processes are customized to each single document, keyphases extracted from our method are highly specific for each document. Experimental results demonstrate that the proposed sequential pattern mining method outperforms existing pattern mining methods in both runtime performance and completeness. Comparisons on keyphrase benchmark datasets also confirm that the proposed document-specific keyphrase extraction method is effective in improving the quality

关键词： Classification Document summarization Keyphrase extraction Sequential pattern mining Wildcards

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Abstracts

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JOURNAL OF SPINAL CORD MEDICINE 2021年第SUPPL 1期44卷 S278-S324页

作者： [Anonymous] Department of Medicine Division of Physical Medicine and Rehabilitation University of Toronto Toronto ON CA KITE - Toronto Rehabilitation Institute University Health Network Toronto ON CA Institute for Health Policy Management and Evaluation University of Toronto Toronto ON CA Rehabilitation Sciences Institute University of Toronto Toronto ON CA Institute of Medical Sciences University of Toronto Toronto ON CA. Rehabilitation Sciences Institute University of Toronto ON CA KITE Research Institute-Toronto Rehab-University Health Network Toronto ON CA Physical Therapy Department University of Toronto ON CA Praxis Spinal Cord Institute Vancouver BC Université de Montréal (École de réadaptation) Montreal QC CA Institut de réadaptation Gingras-Linsay-de-Montréal Montreal QC CA Division of Physical Medicine & Rehabilitation Department of Medicine Faculty of Medicine & Dentistry University of Alberta Edmonton AB CA University of Calgary Calgary AB CA Alberta Health Services Centre for Family Medicine Kitchener ON CA McMaster University Department of Family Medicine Hamilton ON CA Dept. of Physical Therapy University of Toronto Toronto ON CA KITE-University Health Network Toronto ON CA Praxis Spinal Cord Institute Vancouver BC CA Center for Interdisciplinary Research in Rehabilitation and Social Integration (CIRRIS) Quebec City QC CA Dept. of Rehabilitation Laval University Quebec City QC CA Institute of Health Policy Management and Evaluation University of Toronto Toronto ON CA School of Rehabilitation Science University of Saskatchewan Saskatoon SK CA Ontario Neurotrauma Foundation Toronto ON CA Canadian Spinal Research Organization Toronto ON CA CIUSSS du Centre-Sud-de-l ‘Île-de-Montréal (Installation Gingras-Lindsay) Montréal QC CA École de réadaptation Université de Montréal Montréal QC CA First Steps Wellness Centre Regina SK CA Stan Cassidy Centre for Rehabilitation Horizon Health Network Fredericton NB CA Departmen

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