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    Efficient Disk-Based Techniques for Manipulating Very Large String Databases

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    AminAllam_Dissertation.pdf
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    Type
    Dissertation
    Authors
    Allam, Amin cc
    Advisors
    Kalnis, Panos cc
    Committee members
    Gao, Xin cc
    Moshkov, Mikhail cc
    Mokbel, Mohamed
    Program
    Computer Science
    KAUST Department
    Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division
    Date
    2017-05-18
    Permanent link to this record
    http://hdl.handle.net/10754/623691
    
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    Abstract
    Indexing and processing strings are very important topics in database management. Strings can be database records, DNA sequences, protein sequences, or plain text. Various string operations are required for several application categories, such as bioinformatics and entity resolution. When the string count or sizes become very large, several state-of-the-art techniques for indexing and processing such strings may fail or behave very inefficiently. Modifying an existing technique to overcome these issues is not usually straightforward or even possible. A category of string operations can be facilitated by the suffix tree data structure, which basically indexes a long string to enable efficient finding of any substring of the indexed string, and can be used in other operations as well, such as approximate string matching. In this document, we introduce a novel efficient method to construct the suffix tree index for very long strings using parallel architectures, which is a major challenge in this category. Another category of string operations require clustering similar strings in order to perform application-specific processing on the resulting possibly-overlapping clusters. In this document, based on clustering similar strings, we introduce a novel efficient technique for record linkage and entity resolution, and a novel method for correcting errors in a large number of small strings (read sequences) generated by the DNA sequencing machines.
    Citation
    Allam, A. (2017). Efficient Disk-Based Techniques for Manipulating Very Large String Databases. KAUST Research Repository. https://doi.org/10.25781/KAUST-58MOX
    DOI
    10.25781/KAUST-58MOX
    ae974a485f413a2113503eed53cd6c53
    10.25781/KAUST-58MOX
    Scopus Count
    Collections
    PhD Dissertations; Computer Science Program; Computer, Electrical and Mathematical Science and Engineering (CEMSE) Division

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