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    Cognitive Intelligence in Relational Databases

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    Athley_umbc_0434M_11692.pdf (3.261Mb)
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    http://hdl.handle.net/11603/15494
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    • UMBC Theses and Dissertations
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    Author/Creator
    Unknown author
    Date
    2017-01-01
    Type of Work
    Text
    thesis
    Department
    Computer Science and Electrical Engineering
    Program
    Computer Science
    Rights
    This item may be protected under Title 17 of the U.S. Copyright Law. It is made available by UMBC for non-commercial research and education. For permission to publish or reproduce, please see http://aok.lib.umbc.edu/specoll/repro.php or contact Special Collections at speccoll(at)umbc.edu
    Distribution Rights granted to UMBC by the author.
    Subjects
    cognitive querying
    databases
    word2vec
    Word embedding
    Abstract
    We evaluate the applicability of distributed language embedding techniques from the domain of natural language processing to relational data. Relational data is typically stored in SQL databases. We apply modern distributed representations of words (Tomas Mikolov 2013c) and paragraph (Quoc V. Le 2014) techniques to this structured data and attempt to unlock the potential of enhanced cognitive querying. The research intention is to be able to perform queries which are non-trivial to perform using the SQL dialect alone. We tokenize the IMDB 5000 movie data-set to generate embeddings using word2vec and a modified version of doc2vec that we term as row2vec. We discuss the effects of various hyperparameter choices and tokenization techniques. We visualise these embedding using PCA and present the results for certain queries. Keywords: Word embedding, databases, word2vec, cognitive querying.


    Albin O. Kuhn Library & Gallery
    University of Maryland, Baltimore County
    1000 Hilltop Circle
    Baltimore, MD 21250
    www.umbc.edu/scholarworks

    Contact information:
    Email: scholarworks-group@umbc.edu
    Phone: 410-455-3544


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    Albin O. Kuhn Library & Gallery
    University of Maryland, Baltimore County
    1000 Hilltop Circle
    Baltimore, MD 21250
    www.umbc.edu/scholarworks

    Contact information:
    Email: scholarworks-group@umbc.edu
    Phone: 410-455-3544


    If you wish to submit a copyright complaint or withdrawal request, please email mdsoar-help@umd.edu.