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Measuring the quality of unstructured text in routinely collected electronic health data: a review and application
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LEXICON BASED RULE EXTRACTION FOR SENTIMENT ANALYSIS UNDER BIG DATA ENVIRONMENT ...
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LEXICON BASED RULE EXTRACTION FOR SENTIMENT ANALYSIS UNDER BIG DATA ENVIRONMENT ...
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NgramPOS: A Bigram-based Linguistic and Statistical Feature Process Model for Unstructured Text Classification
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Big Data Text Summarization: Using Deep Learning to Summarize Theses and Dissertations
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Face value of companies: deep learning for nonverbal communication ...
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Face value of companies: deep learning for nonverbal communication
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Supervised Process of Un-structured Data Analysis for Knowledge Chaining
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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)
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Leveraging Lexical Link Analysis (LLA) To Discover New Knowledge
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In: Military Cyber Affairs (2016)
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A Corpus Driven Computational Intelligence Framework for Deception Detection in Financial Text
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Sentiment Big Data Flow Analysis by Means of Dynamic Linguistic Patterns
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Lexical Link Analysis Application: Improving Web Service to Acquisition Visibility Portal
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In: DTIC (2013)
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Automated Extraction and Characterisation of Social Network Data from Unstructured Sources -- An Ontology-Based Approach
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In: DTIC (2013)
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Applications of Lexical Link Analysis Web Service for Large-Scale Automation, Validation, Discovery, Visualization, and Real-Time Program Awareness
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In: DTIC (2012)
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System Self-Awareness and Related Methods for Improving the Use and Understanding of Data within DoD
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Collective knowledge systems: Where the social web meets the semantic web
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In: http://www.websemanticsjournal.org/papers/2007119/CollectiveKnowledgeSystemsGruberV6I1.pdf (2008)
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A conceptual-modeling approach to extracting data from the web
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In: http://www.deg.byu.edu/papers/er98.pdf (1998)
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Abstract:
Electronically available data on the Web is exploding at an ever increasing pace. Much of this data is unstructured, which makes searching hard and traditional database querying impossible. Many Web documents, however, contain an abundance of recognizable constants that together describe the essence of a document’s content. For these kinds of data-rich documents (e.g., advertisements, movie reviews, weather reports, travel information, sports summaries, financial statements, obituaries, and many others) we can apply a conceptual-modeling approach to extract and structure data. The approach is based on an ontology—a conceptual model instance—that describes the data of interest, including relationships, lexical appearance, and context
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Keyword:
data extraction; data structuring; data-rich document; obituary; ontological conceptual modeling; ontology; unstructured data; World-Wide Web
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URL: http://www.deg.byu.edu/papers/er98.pdf http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.67.3888
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A Conceptual-Modeling Approach to Extracting Data from the Web
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In: http://osm7.cs.byu.edu/deg/papers/er98.ps (1998)
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A Conceptual-Modeling Approach to Extracting Data from the Web
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In: http://lantern.cs.byu.edu/papers/er98.ps (1998)
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