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題名 Monitoring Heterogeneous Nearest Neighbors for Moving Objects Considering Location-Independent Attributes 作者 Y-C- Su;Y-H- Wu;陳良弼 關鍵詞 Heterogeneous 日期 2007 上傳時間 16-Dec-2008 16:46:44 (UTC+8) 摘要 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. 關聯 Lecture Notes in Computer Science, 4443, 300-312 資料類型 article dc.creator (作者) Y-C- Su;Y-H- Wu;陳良弼 en_US dc.date (日期) 2007 en_US dc.date.accessioned 16-Dec-2008 16:46:44 (UTC+8) - dc.date.available 16-Dec-2008 16:46:44 (UTC+8) - dc.date.issued (上傳時間) 16-Dec-2008 16:46:44 (UTC+8) - dc.identifier.uri (URI) https://nccur.lib.nccu.edu.tw/handle/140.119/15007 - dc.description.abstract (摘要) 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. - dc.format application/ en_US dc.language en en_US dc.language en-US en_US dc.language.iso en_US - dc.relation (關聯) Lecture Notes in Computer Science, 4443, 300-312 en_US dc.subject (關鍵詞) Heterogeneous - dc.title (題名) Monitoring Heterogeneous Nearest Neighbors for Moving Objects Considering Location-Independent Attributes en_US dc.type (資料類型) article en
