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dc.contributor.advisorRamanan, Prakash
dc.contributor.authorSingh, Sanjaya
dc.descriptionThesis (M.S.)--Wichita State University, College of Engineering, Dept. of Electrical Engineering and Computer Science.en_US
dc.description.abstractData entities from various data sources could be ordered according to a variety of attributes associated with those entities. These orderings result in a ranking of entities in terms of the values in the attribute domains. In query processing, user preferences are desired to be tied to values of specific rank attributes. A way to incorporate such preference is by utilizing a function f that combines user preferences and rank attribute values and returns numerical value. Top-k queries seek to identify the tuples with the highest numerical value. We consider the top-k selection query on relational database: SELECT * FROM S ORDER BY f(t) LIMIT k.We propose efficient indexes on S to find the top-k tuples, for a given linear monotone preference function f . The efficiency of our approach depends on the number of dimensions: the number of rank attributes used to compute f . We present efficient algorithms for two dimensions. Our results for two dimensions improve upon Tsaparas et. al. Our approach is based on convex layers, which is more appropriate for linear preference function.en_US
dc.format.extentviii, 42 p.en
dc.publisherWichita State Universityen_US
dc.rightsCopyright Sanjaya Singh, 2011. All rights reserveden
dc.subject.lcshElectronic dissertationsen
dc.titleRanked selection indexes for linear preference queriesen_US

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  • CE Theses and Dissertations
    Doctoral and Master's theses authored by the College of Engineering graduate students
  • EECS Theses and Dissertations
    Collection of Master's theses and Ph.D. dissertations completed at the Dept. of Electrical Engineering and Computer Science
  • Master's Theses
    This collection includes Master's theses completed at the Wichita State University Graduate School (Fall 2005 --)

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