Group k- Nearest Neighbor Query Method for Uncertainty Data in Obstructed Spaces
To deal with the problem of group k nearest neighbor query method for uncertainty data in obstructed spaces, this paper presents the method of the PkOGNN(probabilistic k obstructed group nearest neighbor)query .The PkOGNN query method mainly includes four sub-algorithms: Compadist_o(),SpatialPru(...
Saved in:
| Main Authors: | , , , , |
|---|---|
| Format: | Article |
| Language: | zho |
| Published: |
Harbin University of Science and Technology Publications
2019-06-01
|
| Series: | Journal of Harbin University of Science and Technology |
| Subjects: | |
| Online Access: | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1678 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| _version_ | 1849341072827744256 |
|---|---|
| author | WAN Jing TANG Bei-bei SUN Jian HE Yun-bin LI Song |
| author_facet | WAN Jing TANG Bei-bei SUN Jian HE Yun-bin LI Song |
| author_sort | WAN Jing |
| collection | DOAJ |
| description | To deal with the problem of group k nearest neighbor query method for uncertainty data in obstructed spaces, this paper presents the method of the PkOGNN(probabilistic k obstructed group nearest neighbor)query .The PkOGNN query method mainly includes four sub-algorithms: Compadist_o(),SpatialPru(),PruInterEnt() and PkOGNN(), These algorithms are respectively the calculation of the aggregate obstructed distance, the spatial pruning method, the pruning of the R-tree intermediate items according to the spatial pruning method, the final refined query method. It integrates the effective pruning methods to reduce the search space of PkOGNN and get the correct kGNNs.The theoretical research and experimental results show that the proposed method has good efficiency. |
| format | Article |
| id | doaj-art-8da9da5c789d4fea8f302e965dee0241 |
| institution | Kabale University |
| issn | 1007-2683 |
| language | zho |
| publishDate | 2019-06-01 |
| publisher | Harbin University of Science and Technology Publications |
| record_format | Article |
| series | Journal of Harbin University of Science and Technology |
| spelling | doaj-art-8da9da5c789d4fea8f302e965dee02412025-08-20T03:43:43ZzhoHarbin University of Science and Technology PublicationsJournal of Harbin University of Science and Technology1007-26832019-06-012403293410.15938/j.jhust.2019.03.005Group k- Nearest Neighbor Query Method for Uncertainty Data in Obstructed SpacesWAN Jing0TANG Bei-bei1SUN Jian2HE Yun-bin3LI Song4School of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,ChinaSchool of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,ChinaSchool of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,ChinaSchool of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,ChinaSchool of Computer Science and Technology,Harbin University of Science and Technology,Harbin 150080,ChinaTo deal with the problem of group k nearest neighbor query method for uncertainty data in obstructed spaces, this paper presents the method of the PkOGNN(probabilistic k obstructed group nearest neighbor)query .The PkOGNN query method mainly includes four sub-algorithms: Compadist_o(),SpatialPru(),PruInterEnt() and PkOGNN(), These algorithms are respectively the calculation of the aggregate obstructed distance, the spatial pruning method, the pruning of the R-tree intermediate items according to the spatial pruning method, the final refined query method. It integrates the effective pruning methods to reduce the search space of PkOGNN and get the correct kGNNs.The theoretical research and experimental results show that the proposed method has good efficiency.https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1678r-treegroup nearest neighbor queryuncertaintyvisibilityobstructed distance |
| spellingShingle | WAN Jing TANG Bei-bei SUN Jian HE Yun-bin LI Song Group k- Nearest Neighbor Query Method for Uncertainty Data in Obstructed Spaces Journal of Harbin University of Science and Technology r-tree group nearest neighbor query uncertainty visibility obstructed distance |
| title | Group k- Nearest Neighbor Query Method for Uncertainty Data in Obstructed Spaces |
| title_full | Group k- Nearest Neighbor Query Method for Uncertainty Data in Obstructed Spaces |
| title_fullStr | Group k- Nearest Neighbor Query Method for Uncertainty Data in Obstructed Spaces |
| title_full_unstemmed | Group k- Nearest Neighbor Query Method for Uncertainty Data in Obstructed Spaces |
| title_short | Group k- Nearest Neighbor Query Method for Uncertainty Data in Obstructed Spaces |
| title_sort | group k nearest neighbor query method for uncertainty data in obstructed spaces |
| topic | r-tree group nearest neighbor query uncertainty visibility obstructed distance |
| url | https://hlgxb.hrbust.edu.cn/#/digest?ArticleID=1678 |
| work_keys_str_mv | AT wanjing groupknearestneighborquerymethodforuncertaintydatainobstructedspaces AT tangbeibei groupknearestneighborquerymethodforuncertaintydatainobstructedspaces AT sunjian groupknearestneighborquerymethodforuncertaintydatainobstructedspaces AT heyunbin groupknearestneighborquerymethodforuncertaintydatainobstructedspaces AT lisong groupknearestneighborquerymethodforuncertaintydatainobstructedspaces |