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    Please use this identifier to cite or link to this item: https://nccur.lib.nccu.edu.tw/handle/140.119/15007


    Title: Monitoring Heterogeneous Nearest Neighbors for Moving Objects Considering Location-Independent Attributes
    Authors: Y-C- Su;Y-H- Wu;陳良弼
    Keywords: Heterogeneous
    Date: 2007
    Issue Date: 2008-12-16 16:46:44 (UTC+8)
    Abstract: In some applications, data may possess both location-dependent and location-independent attributes. For example, in a job database, each job can be associated with both location-dependent attributes, e.g., the location of the work place, and location-independent ones, e.g., the salary. A person who uses this database to find a job may prefer not only a shorter distance between his/her house and the work place but also a higher salary. Therefore, a query with both concepts of “shorter distance” and “higher salary” should be considered to meet the user’s needs. We call it the heterogeneous k-nearest neighbor (HkNN) query in distinction from the traditional k-nearest neighbor (kNN) query in the spatial domain, which only concerns location-dependent attributes. To our knowledge, this paper is the first work proposing a generic framework for solving the HkNN query. We propose an efficient approach based on the bounding property for the HkNN query evaluation. Furthermore, we provide an update mechanism for continuously monitoring the HkNN queries in a dynamic environment. Experimental results verify that the proposed framework is both efficient and scalable.
    Relation: Lecture Notes in Computer Science, 4443, 300-312
    Data Type: article
    Appears in Collections:[Department of Computer Science ] Periodical Articles

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