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Spatial Queries Based on Non-Spatial Constraints

Spatial Queries Based on Non-Spatial Constraints


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About the Book

This dissertation, "Spatial Queries Based on Non-spatial Constraints" by Xiangyuan, Dai, 戴祥元, was obtained from The University of Hong Kong (Pokfulam, Hong Kong) and is being sold pursuant to Creative Commons: Attribution 3.0 Hong Kong License. The content of this dissertation has not been altered in any way. We have altered the formatting in order to facilitate the ease of printing and reading of the dissertation. All rights not granted by the above license are retained by the author. Abstract: Abstract of thesis entitled Spatial Queries Based on Non-Spatial Constraints Submitted by Dai Xiangyuan for the degree of Master of Philosophy at The University of Hong Kong in December 2006 Spatial database research has been evolving for the last two decades, and many commercial database products (e.g. GIS, Oracle, Illustra, Postgress, Mapinfo) have been developed to meet people's increasing needs for spatial data management and analysis. Conventional spatial queries (e.g. spatial range queries, nearest neighbor queries)onlydealwithspatialfeatures(e.g. location, shape)ofobjects, while little attention has been paid to the type of spatial queries which are based on non-spatial features (e.g. name, size, type, price). However, these kinds of query have many practical applications, and due attention needs to be paid by researchers from both the academic and industrial fields. A common example of spatial queries that involve non-spatial features is related to remote sensing. Consider a satellite image, where interesting objects (e.g., vessels) have been extracted (e.g., by a human expert or animage segmentation tool). Due to low image resolution and/or color defini- tions, the data extractor may not be 100% certain whether a pixel formation corresponds to an actual object x. A probability E could therefore be as- signed to x, reflecting the confidence of x's existence. We call such objects existentially uncertain. In such a situation, suppose that a port officer wants to find a set of vessels S such that every x ∈ S is the nearest ship to the port with confidence at least 30%. Here, the evaluation process of the above spatial queries are highly affected by a non-spatial feature (the existential uncertainty of the objects). Anotherexampleofthequerieswestudyinthisthesisisrelatedtothereal estate industry. Consider a real estate agency office that holds a database of available flats for lease. A customer may want to rank the flats with respect to the appropriateness of their locations, defined after aggregating the qualities of other features (e.g. restaurants, cafes, hospitals, markets) withinadistancerangefromthem. Asinthepreviousexample, anon-spatial feature (the qualities in the neighborhood) affects the query results. In this thesis, we formally study spatial queries based on non-spatial constraints and select two query types within this field to conduct our in- depth analysis: (i) Probabilistic Spatial Queries on Existentially Uncertain Data and (ii) Top-k Spatial Preference Queries. We propose adaptations of spatial access methods and search algorithms for probabilistic spatial queries on existentially uncertain data and compare them experimentally. For top-k spatial preference queries, we investigate appropriate indexing techniques and invent new search algorithms. Thestudymakesanimportantnewcontributiontotheresearchonspatial databases, and suggests promising future avenues of exploration, and draws attention to potentially useful practical applications. An abstract of exactly 432 words Signed..................................... Dai Xiangyuan DOI: 10.5353/th_b3843639 Subjects: Query languages (Computer science) Algorithms


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Product Details
  • ISBN-13: 9781361434352
  • Publisher: Open Dissertation Press
  • Publisher Imprint: Open Dissertation Press
  • Height: 279 mm
  • No of Pages: 114
  • Weight: 558 gr
  • ISBN-10: 136143435X
  • Publisher Date: 27 Jan 2017
  • Binding: Hardback
  • Language: English
  • Spine Width: 8 mm
  • Width: 216 mm


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