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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Page: 1 2 Hits 1 – 20 of 24 1 Measuring the quality of unstructured text in routinely collected electronic health data: a review and application Nesca, Marcello. - 2022 BASE Show details 2 LEXICON BASED RULE EXTRACTION FOR SENTIMENT ANALYSIS UNDER BIG DATA ENVIRONMENT ... B. Sevugamoorthy. - : Zenodo, 2019 BASE Show details 3 LEXICON BASED RULE EXTRACTION FOR SENTIMENT ANALYSIS UNDER BIG DATA ENVIRONMENT ... B. Sevugamoorthy. - : Zenodo, 2019 BASE Show details 4 NgramPOS: A Bigram-based Linguistic and Statistical Feature Process Model for Unstructured Text Classification Lau, Sian; Yazdania, Sepideh; Tan, Zhiyuan. - : BMC, 2018 BASE Show details 5 Big Data Text Summarization: Using Deep Learning to Summarize Theses and Dissertations Kahu, Sampanna; Ingram, William A.; Jude, Palakh. - : Virginia Tech, 2018 BASE Show details 6 Face value of companies: deep learning for nonverbal communication ... Burgard, Sophie. - : Humboldt-Universität zu Berlin, 2017 BASE Show details 7 Face value of companies: deep learning for nonverbal communication Burgard, Sophie. - : Humboldt-Universität zu Berlin, 2017 BASE Show details 8 Supervised Process of Un-structured Data Analysis for Knowledge Chaining Quantin, Matthieu; Hervy, Benjamin; Laroche, Florent... In: Procedia CIRP ; CIRP design conference ; https://hal.archives-ouvertes.fr/hal-01347030 ; CIRP design conference, KTH, Jun 2016, Stockholm, Sweden. pp.436-441, ⟨10.1016/j.procir.2016.04.123⟩ ; http://cirpdesign2016.org/ (2016) BASE Show details 9 Leveraging Lexical Link Analysis (LLA) To Discover New Knowledge Zhao, Ying; MacKinnon, Douglas J.; Gallup, Shelley P.... In: Military Cyber Affairs (2016) BASE Show details 10 A Corpus Driven Computational Intelligence Framework for Deception Detection in Financial Text Minhas, Saliha Z. - : University of Stirling, 2016 BASE Show details 11 Situation Tracking in Large Data Streams Smith, Andrew; Wiles, Janet In: DTIC (2015) BASE Show details 12 Sentiment Big Data Flow Analysis by Means of Dynamic Linguistic Patterns Hussain, Amir; Bisio, Federica; Gelbukh, Alexander. - : IEEE, 2015 BASE Show details 13 Lexical Link Analysis Application: Improving Web Service to Acquisition Visibility Portal Zhao, Ying; Gallup, Shelley P; MacKinnon, Douglas J In: DTIC (2013) BASE Show details 14 Automated Extraction and Characterisation of Social Network Data from Unstructured Sources -- An Ontology-Based Approach Martineau, Etienne; Lecocq, Regine In: DTIC (2013) BASE Show details 15 Applications of Lexical Link Analysis Web Service for Large-Scale Automation, Validation, Discovery, Visualization, and Real-Time Program Awareness Zhao, Ying; Gallup, Shelley P; MacKinnon, Douglas J In: DTIC (2012) BASE Show details 16 System Self-Awareness and Related Methods for Improving the Use and Understanding of Data within DoD Zhao, Ying; Mackinnon, Douglas J.; Gallup, Shelley P.. - 2011 BASE Show details 17 Collective knowledge systems: Where the social web meets the semantic web Tom Gruber In: http://www.websemanticsjournal.org/papers/2007119/CollectiveKnowledgeSystemsGruberV6I1.pdf (2008) Abstract: Abstract: What can happen if we combine the best ideas from the Social Web and Semantic Web? The Social Web is an ecosystem of participation, where value is created by the aggregation of many individual user contributions. The Semantic Web is an ecosystem of data, where value is created by the integration of structured data from many sources. What applications can best synthesize the strengths of these two approaches, to create a new level of value that is both rich with human participation and powered by well-structured information? This paper proposes a class of applications called collective knowledge systems, which unlock the "collective intelligence " of the Social Web with knowledge representation and reasoning techniques of the Semantic Web. Keyword: Collected Intelligence; Collective intelligence; Collective Knowledge Systems; human-machine systems; Learning from Semistructured Data; RealTravel; Snap-to-grid; Socio-Semantic Web Keywords; Special Issue; structured and unstructured data; TagCommons; Title; Travel recommendation engine; Web 3.0; Where the Social Web meets the Semantic Web Article Type URL: http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.106.183 http://www.websemanticsjournal.org/papers/2007119/CollectiveKnowledgeSystemsGruberV6I1.pdf BASE Hide details 18 A conceptual-modeling approach to extracting data from the web D. W. Embley; D. M. Campbell; Y. S. Jiang... In: http://www.deg.byu.edu/papers/er98.pdf (1998) BASE Show details 19 A Conceptual-Modeling Approach to Extracting Data from the Web D.W. Embley; D.M. Campbell; Y.S. Jiang... In: http://osm7.cs.byu.edu/deg/papers/er98.ps (1998) BASE Show details 20 A Conceptual-Modeling Approach to Extracting Data from the Web Embley Campbell; D. W. Embley; D. M. Campbell... In: http://lantern.cs.byu.edu/papers/er98.ps (1998) BASE Show details Page: 1 2

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