Dynamic reverse furthest neighbor querying algorithm of moving objects

Li, Bohan, Zhang, Chao, Chen, Weitong, Yang, Yingbao, Feng, Shaohong, Zhang, Qiqian, Yuan, Weiwei and Li, Dongjing (2016). Dynamic reverse furthest neighbor querying algorithm of moving objects. In: Advanced Data Mining and Applications - 12th International Conference, ADMA 2016, Proceedings. 12th International Conference on Advanced Data Mining and Applications, ADMA 2016, Gold Coast, QLD, Australia, (266-279). 12-15 December 2016. doi:10.1007/978-3-319-49586-6_18


Author Li, Bohan
Zhang, Chao
Chen, Weitong
Yang, Yingbao
Feng, Shaohong
Zhang, Qiqian
Yuan, Weiwei
Li, Dongjing
Title of paper Dynamic reverse furthest neighbor querying algorithm of moving objects
Conference name 12th International Conference on Advanced Data Mining and Applications, ADMA 2016
Conference location Gold Coast, QLD, Australia
Conference dates 12-15 December 2016
Proceedings title Advanced Data Mining and Applications - 12th International Conference, ADMA 2016, Proceedings   Check publisher's open access policy
Journal name Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)   Check publisher's open access policy
Series Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Place of Publication Heidelberg, Germany
Publisher Springer Verlag
Publication Year 2016
Year available 2016
Sub-type Fully published paper
DOI 10.1007/978-3-319-49586-6_18
Open Access Status Not yet assessed
ISBN 9783319495859
ISSN 1611-3349
0302-9743
Volume 10086 LNAI
Start page 266
End page 279
Total pages 14
Language eng
Abstract/Summary With the development of wireless communications and positioning technologies, locations of moving objects are highly demanding services. The assumption of static data is majorly applied on previous researches on reverse furthest neighbor queries. However, the data are dynamic property in the real world. Even, the data-aware are uncertain due to the limitation of measuring equipment or the delay of data communication. To effectively find the influence of querying a large number of moving objects existing in boundary area vs querying results of global query area, we put forward dynamic reverse furthest neighbor query algorithms and probabilistic reverse furthest neighbor query algorithms. These algorithms can solve the query of weak influence set for moving objects. Furthermore, we investigate the uncertain moving objects model and define a probabilistic reverse furthest neighbor query, and then present a half-plane pruning for individual moving objects and spatial pruning method for uncertain moving objects. The experimental results show that the algorithm is effective, efficient and scalable in different distribution and volume of data sets.
Subjects 2614 Theoretical Computer Science
1700 Computer Science
Keyword Long tail
Moving objects
Pruning
Reverse furthest neighbor
Uncertain moving object
Q-Index Code E1
Q-Index Status Provisional Code
Institutional Status UQ

Document type: Conference Paper
Sub-type: Fully published paper
Collection: School of Information Technology and Electrical Engineering Publications
 
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Created: Sat, 16 Dec 2017, 19:01:03 EST