Literatura científica selecionada sobre o tema "Augmentation de tables"
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Artigos de revistas sobre o assunto "Augmentation de tables"
Wu, Junyi, Chen Ye, Haoshi Zhi e Shihao Jiang. "Column-Type Prediction for Web Tables Powered by Knowledge Base and Text". Mathematics 11, n.º 3 (20 de janeiro de 2023): 560. http://dx.doi.org/10.3390/math11030560.
Texto completo da fonteWang, Jiayi, Chengliang Chai, Nan Tang, Jiabin Liu e Guoliang Li. "Coresets over multiple tables for feature-rich and data-efficient machine learning". Proceedings of the VLDB Endowment 16, n.º 1 (setembro de 2022): 64–76. http://dx.doi.org/10.14778/3561261.3561267.
Texto completo da fonteDobra, Adrian, Claudia Tebaldi e Mike West. "Data augmentation in multi-way contingency tables with fixed marginal totals". Journal of Statistical Planning and Inference 136, n.º 2 (fevereiro de 2006): 355–72. http://dx.doi.org/10.1016/j.jspi.2004.07.002.
Texto completo da fonteChen, Zhiyu. "Dataset Search and Augmentation". ACM SIGIR Forum 56, n.º 1 (junho de 2022): 1–2. http://dx.doi.org/10.1145/3582524.3582544.
Texto completo da fonteBussotti, Jean-Flavien, Enzo Veltri, Donatello Santoro e Paolo Papotti. "Generation of Training Examples for Tabular Natural Language Inference". Proceedings of the ACM on Management of Data 1, n.º 4 (8 de dezembro de 2023): 1–27. http://dx.doi.org/10.1145/3626730.
Texto completo da fonteAhmed, Naveed, Umar Khan, Syed Tauseef Mohyud-Din e Saeed Ullah Jan. "Non-linear radiative squeezed flow in a rotating frame". Engineering Computations 34, n.º 8 (6 de novembro de 2017): 2450–62. http://dx.doi.org/10.1108/ec-04-2017-0158.
Texto completo da fonteSajid, Tanveer, Muhammad Sagheer, Shafqat Hussain e Faisal Shahzad. "Impact of double-diffusive convection and motile gyrotactic microorganisms on magnetohydrodynamics bioconvection tangent hyperbolic nanofluid". Open Physics 18, n.º 1 (2 de maio de 2020): 74–88. http://dx.doi.org/10.1515/phys-2020-0009.
Texto completo da fonteLi, Xiangge, Hong Luo e Yan Sun. "WordBlitz: An Efficient Hard-Label Textual Adversarial Attack Method Jointly Leveraging Adversarial Transferability and Word Importance". Applied Sciences 14, n.º 9 (30 de abril de 2024): 3831. http://dx.doi.org/10.3390/app14093831.
Texto completo da fonteIsmail, Nur Hilwani, Siti Fatimah Ibrahim, Farah Hanan Fathihah Jaffar, Mohd Helmy Mokhtar, Kok Yong Chin e Khairul Osman. "Augmentation of the Female Reproductive System Using Honey: A Mini Systematic Review". Molecules 26, n.º 3 (27 de janeiro de 2021): 649. http://dx.doi.org/10.3390/molecules26030649.
Texto completo da fonteCastelo, Sonia, Rémi Rampin, Aécio Santos, Aline Bessa, Fernando Chirigati e Juliana Freire. "Auctus". Proceedings of the VLDB Endowment 14, n.º 12 (julho de 2021): 2791–94. http://dx.doi.org/10.14778/3476311.3476346.
Texto completo da fonteTeses / dissertações sobre o assunto "Augmentation de tables"
Liu, Jixiong. "Semantic Annotations for Tabular Data Using Embeddings : Application to Datasets Indexing and Table Augmentation". Electronic Thesis or Diss., Sorbonne université, 2023. http://www.theses.fr/2023SORUS529.
Texto completo da fonteWith the development of Open Data, a large number of data sources are made available to communities (including data scientists and data analysts). This data is the treasure of digital services as long as data is cleaned, unbiased, as well as combined with explicit and machine-processable semantics in order to foster exploitation. In particular, structured data sources (CSV, JSON, XML, etc.) are the raw material for many data science processes. However, this data derives from different domains for which consumers are not always familiar with (knowledge gap), which complicates their appropriation, while this is a critical step in creating machine learning models. Semantic models (in particular, ontologies) make it possible to explicitly represent the implicit meaning of data by specifying the concepts and relationships present in the data. The provision of semantic labels on datasets facilitates the understanding and reuse of data by providing documentation on the data that can be easily used by a non-expert. Moreover, semantic annotation opens the way to search modes that go beyond simple keywords and allow the use of queries of a high conceptual level on the content of the datasets but also their structure while overcoming the problems of syntactic heterogeneity encountered in tabular data. This thesis introduces a complete pipeline for the extraction, interpretation, and applications of tables in the wild with the help of knowledge graphs. We first refresh the exiting definition of tables from the perspective of table interpretation and develop systems for collecting and extracting tables on the Web and local files. Three table interpretation systems are further proposed based on either heuristic rules or graph representation models facing the challenges observed from the literature. Finally, we introduce and evaluate two table augmentation applications based on semantic annotations, namely data imputation and schema augmentation
Lehmberg, Oliver [Verfasser], e Christian [Akademischer Betreuer] Bizer. "Web table integration and profiling for knowledge base augmentation / Oliver Lehmberg ; Betreuer: Christian Bizer". Mannheim : Universitätsbibliothek Mannheim, 2019. http://d-nb.info/1197143866/34.
Texto completo da fonteHeyder, Jakob Wendelin. "Knowledge Base Augmentation from Spreadsheet Data : Combining layout inference with multimodal candidate classification". Thesis, KTH, Skolan för elektroteknik och datavetenskap (EECS), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-278824.
Texto completo da fonteKalkylblad består av ett värdefullt och särskilt stort datasätt av dokument inom många företagsorganisationer och på webben. Även om kalkylblad är intuitivt att använda och är utrustad med kraftfulla funktioner, utvinning och transformation av data är fortfarande en besvärlig och manuell uppgift. Den stora flexibiliteten som de ger användaren resulterar i data som är godtyckligt strukturerade och svåra att bearbeta för andra applikationer. I det här förslaget föreslår vi en ny arkitektur som kombinerar övervakad layoutinferens och multimodal kandidatklassificering för att tillåta kunskapsbasförstärkning från godtyckliga kalkylblad. I vår design överväger vi behovet av att reparera felklassificeringar och möjliggöra verifiering och rangordning av tvetydiga kandidater. Vi utvärderar systemets utförande på två datasätt, en med singeltabellkalkylblad, en annan med kalkylblad av godtyckligt format. Utvärderingsresultatet visar att det föreslagna systemet uppnår liknande prestanda på singel-tabellkalkylblad jämfört med state-of-the-art regelbaserade lösningar. Dessutom tillåter systemets flexibilitet oss att bearbeta godtyckliga kalkylark format, inklusive horisontella och vertikala inriktade tabeller, flera kalkylblad och sammanhangsförande metadata. Detta var inte möjligt med existerande rent textbaserade eller tabellbaserade lösningar. Experimenten visar att det kan uppnå hög effektivitet med en F1-poäng på 95.71 på godtyckliga kalkylblad som kräver tolkning av omgivande metadata. Systemets precision kan ökas ytterligare genom att applicera schema-matchning av kandidater baserat på semantisk likhet mellan kolumnrubriker.
Livros sobre o assunto "Augmentation de tables"
United States. National Aeronautics and Space Administration., ed. Experimental and computational investigation of lift-enhancing tabs on a multi-element airfoil. [Stanford, Calif.]: Joint Institute for Aeronautics and Acoustics, National Aeronautics and Space Administration, Ames Research Center, 1996.
Encontre o texto completo da fonteUnited States. National Aeronautics and Space Administration., ed. Experimental and computational investigation of lift-enhancing tabs on a multi-element airfoil. [Stanford, Calif.]: Joint Institute for Aeronautics and Acoustics, National Aeronautics and Space Administration, Ames Research Center, 1996.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Augmentation de tables"
Del Bimbo, Davide, Andrea Gemelli e Simone Marinai. "Data Augmentation on Graphs for Table Type Classification". In Lecture Notes in Computer Science, 242–52. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-23028-8_25.
Texto completo da fonteKhan, Umar, Sohaib Zahid, Muhammad Asad Ali, Adnan Ul-Hasan e Faisal Shafait. "TabAug: Data Driven Augmentation for Enhanced Table Structure Recognition". In Document Analysis and Recognition – ICDAR 2021, 585–601. Cham: Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-86331-9_38.
Texto completo da fonteChen, Bangdong, Dezhi Peng, Jiaxin Zhang, Yujin Ren e Lianwen Jin. "Complex Table Structure Recognition in the Wild Using Transformer and Identity Matrix-Based Augmentation". In Frontiers in Handwriting Recognition, 545–61. Cham: Springer International Publishing, 2022. http://dx.doi.org/10.1007/978-3-031-21648-0_37.
Texto completo da fonteMehl-Schneider, Toby B. "Recent Advances in Augmentative and Alternative Communication". In Advances in Medical Technologies and Clinical Practice, 128–40. IGI Global, 2015. http://dx.doi.org/10.4018/978-1-4666-8395-2.ch006.
Texto completo da fonteZhu, Wei, Charles B. Owen, Hairong Li e Joo-Hyun Lee. "Design of the PromoPad". In Advances in End User Computing, 193–205. IGI Global, 2010. http://dx.doi.org/10.4018/978-1-60566-687-7.ch011.
Texto completo da fonte"Faithful extension of a relation, bivalent tableau, faithful augmentation, Szpilrajn chain". In Theory of Relations, 223–39. Elsevier, 2000. http://dx.doi.org/10.1016/s0049-237x(00)80055-5.
Texto completo da fonteWunder, Iris, e Ruth Maloszek. "Perspective Chapter: iPEAR-MOOC". In Massive Open Online Courses - Current Practice and Future Trends [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.1001463.
Texto completo da fontePlattard, Serge. "L’ONU et l’espace". In Annuaire français de relations internationales, 887–903. Éditions Panthéon-Assas, 2023. http://dx.doi.org/10.3917/epas.ferna.2023.01.0887.
Texto completo da fonteKonstantinou, Gerasimos, e Mohamed Attia. "Perspective Chapter: From the Boom to Gen Z – Has Depression Changed across Generations?" In Depression - What Is New and What Is Old in Human Existence [Working Title]. IntechOpen, 2023. http://dx.doi.org/10.5772/intechopen.1003091.
Texto completo da fonteD., Aju, Anil Kumar Kakelli, Ashwin Suresh Varma e Kishore Rajendiran. "A Comprehensive Perspective on Mobile Forensics". In Advances in Digital Crime, Forensics, and Cyber Terrorism, 1–28. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4900-1.ch001.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Augmentation de tables"
Weger, Marian, Thomas Hermann e Robert Höldrich. "AltAR/Table: A Platform for Plausible Auditory Augmentation". In ICAD 2022: The 27th International Conference on Auditory Display. icad.org: International Community for Auditory Display, 2022. http://dx.doi.org/10.21785/icad2022.005.
Texto completo da fonteDreossi, Tommaso, Shromona Ghosh, Xiangyu Yue, Kurt Keutzer, Alberto Sangiovanni-Vincentelli e Sanjit A. Seshia. "Counterexample-Guided Data Augmentation". In Twenty-Seventh International Joint Conference on Artificial Intelligence {IJCAI-18}. California: International Joint Conferences on Artificial Intelligence Organization, 2018. http://dx.doi.org/10.24963/ijcai.2018/286.
Texto completo da fonteKavitha, K. M., Vaishnavi Naik, Sahana Angadi, Sandra Satish e Suman Nayak. "Hybrid Approaches for Augmentation of Translation Tables for Indian Languages". In 2020 19th IEEE International Conference on Machine Learning and Applications (ICMLA). IEEE, 2020. http://dx.doi.org/10.1109/icmla51294.2020.00157.
Texto completo da fonteChen, Haipeng, Sushil Jajodia, Jing Liu, Noseong Park, Vadim Sokolov e V. S. Subrahmanian. "FakeTables: Using GANs to Generate Functional Dependency Preserving Tables with Bounded Real Data". In Twenty-Eighth International Joint Conference on Artificial Intelligence {IJCAI-19}. California: International Joint Conferences on Artificial Intelligence Organization, 2019. http://dx.doi.org/10.24963/ijcai.2019/287.
Texto completo da fonteCao, Jianhao, Tamara Munzner e Rachel Pottinger. "Visualizing a Tabular Data Repository to Facilitate Descriptive Tag Augmentation for New Tables". In SIGMOD/PODS '23: International Conference on Management of Data. New York, NY, USA: ACM, 2023. http://dx.doi.org/10.1145/3597465.3605226.
Texto completo da fontePham, Minh, Craig A. Knoblock, Muhao Chen, Binh Vu e Jay Pujara. "SPADE: A Semi-supervised Probabilistic Approach for Detecting Errors in Tables". In Thirtieth International Joint Conference on Artificial Intelligence {IJCAI-21}. California: International Joint Conferences on Artificial Intelligence Organization, 2021. http://dx.doi.org/10.24963/ijcai.2021/488.
Texto completo da fonteFrame, Mary, Jessica Armstrong e Bradley Schlessman. "Decision Support Systems for Route Planning: Impacts on Performance and Trust". In 13th International Conference on Applied Human Factors and Ergonomics (AHFE 2022). AHFE International, 2022. http://dx.doi.org/10.54941/ahfe1001562.
Texto completo da fontePillai, Prashanth, e Purnaprajna Mangsuli. "Document Layout Analysis Using Detection Transformers". In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207266-ms.
Texto completo da fonteDai, Chaofan, Qideng Tang, Wubin Ma, Yahui Wu, Haohao Zhou e Huahua Ding. "PromptER: Prompt Contrastive Learning for Generalized Entity Resolution". In 11th International Conference on Artificial Intelligence and Applications. Academy & Industry Research Collaboration Center, 2024. http://dx.doi.org/10.5121/csit.2024.140102.
Texto completo da fonteWeger, Marian, Thomas Hermann e Robert Höldrich. "Plausible Auditory Augmentation of Physical Interaction". In The 24th International Conference on Auditory Display. Arlington, Virginia: The International Community for Auditory Display, 2018. http://dx.doi.org/10.21785/icad2018.024.
Texto completo da fonteRelatórios de organizações sobre o assunto "Augmentation de tables"
DEPARTMENT OF THE ARMY WASHINGTON DC. Army Policies and Procedures for Establishing Multiple Component Modification Table of Organization and Equipment (MTOE) and Augmentation Tables of Distribution (AUGTDAs) Units. Fort Belvoir, VA: Defense Technical Information Center, julho de 2001. http://dx.doi.org/10.21236/ada402529.
Texto completo da fonte