Querying spatial data by dominators in neighborhood. (September 2018)

• Record Type: Journal Article
• Authors: Lu, Hua; Yiu, Man Lung; Xie, Xike
• Is Part Of: Information systems. Volume 77(2018)
• Page Start: 71
• Page End: 85
• Publication Date: 2018-09
• Subjects: Querying spatial data -- Neighborhood dominators -- Spatial data management; Database management -- Periodicals; Electronic data processing -- Periodicals; Bases de données -- Gestion -- Périodiques; Informatique -- Périodiques; Database management; Electronic data processing; Periodicals; 005.7
• DOI: 10.1016/j.is.2018.06.001
• Languages: English
• ISSNs: 0306-4379

Abstract

Highlights: A generic problem of querying spatial objects with respect to their neighboring dominators. Meaningful score functions for ranking spatial objects with respect to their neighboring dominators. Generic algorithm frameworks for querying the spatial objects accordingly. Effective search bounds that allow the different score functions to be supported by the generic querying frameworks. Support for the generic distance and alternative score functions in the generic querying frameworks. Extensive experiments of the proposals, using both synthetic and real data. Abstract: Spatial objects in reality are often associated with geographic locations (e.g., longitude and latitude) as well as multiple quality attributes. Quality attributes make it possible to compare spatial objects according to the dominance concept. Specifically, an object pi is said to dominate another object pj if pi is no worse than pj on all quality attributes and better than pj on at least one quality attribute. In many contexts, an object's dominators in its neighborhood indicate the negative effect to the object. In this paper, we study the problem of querying spatial objects by their dominators in the neighborhood. We propose three meaningful score functions to quantify the negative effects of dominators in a spatial object's neighborhood. The most endangered object (MEO) query thus defined has multiple practical applications such as business planning, online war games, and wild animal protection. For processing MEO queries, we design several algorithms that require different indexes on spatial data sets. Each algorithm is generic and flexible such that each can support all three score functions (and even more) without significant changes. We conduct extensive experiments to evaluate the algorithms. The experimental results disclose the performance differences of the algorithms under various settings.