计算机科学 ›› 2015, Vol. 42 ›› Issue (1): 201-205.doi: 10.11896/j.issn.1002-137X.2015.01.045
王丽,秦小麟,许建秋
WANG Li, QIN Xiao-lin and XU Jian-qiu
摘要： 室内空间变得越发的庞大和复杂,随之产生了越来越多的室内空间查询需求。目前已有文献提出了针对室内空间环境的范围查询和最近邻查询, 而作为常见的空间查询类型的反向最近邻查询,尚未有相关的研究。为此,提出了室内概率阈值反向最近邻查询和基于定位设备的设备可达图模型。在图模型基础上,提出了室内概率阈值反向最近邻查询处理算法,该算法由基于图模型的批量剪枝、基于室内距离的剪枝、基于概率的剪枝和概率计算4部分构成,通过剪枝策略修剪掉不可能出现在结果集中的对象,从而缩小了查询空间,提高了效率。
| [1] Jensen C S,Li K J,Winter S.The other 87%:a report on The Second International Workshop on Indoor Spatial Awareness (San Jose,California-November 2,2010)[J].SIGSPATIAL Special,2011,3(1):10-12 [2] http://finance.sina.com.cn/money/consume9/20041025/10361104770.shtml [3] Yang B,Lu H,Jensen C S.Scalable continuous range monitoring of moving objects in symbolic indoor space[C]∥Proceedings of the 18th ACM Conference on Information and Knowledge Mana-gement.ACM,2009:671-680 [4] Lu H,Yang B,Jensen C S.Spatio-temporal joins on symbolic in-door tracking data[C]∥2011 IEEE 27th International Confe-rence on Data Engineering (ICDE).IEEE,2011:816-827 [5] Yuan W,Schneider M.Supporting continuous range queries in indoor space[C]∥2010 Eleventh International Conference on Mobile Data Management (MDM).IEEE,2010:209-214 [6] Lu H,Cao X,Jensen C S.A foundation for efficient indoor distance-aware query processing[C]∥2012 IEEE 28th InternationalConference on Data Engineering (ICDE).IEEE,2012:438-449 [7] Yu J,Ku W S,Sun M T,et al.An RFID and particle filter-based indoor spatial query evaluation system[C]∥Proceedings of the 16th International Conference on Extending Database Technology.ACM,2013:263-274 [8] Xie X,Lu H,Pedersen T B.Efficient distance-aware query eva-luation on indoor moving objects[C]∥ICDE.2013 [9] 甘早斌,袁永光,赵贻竹,等.基于DR-tree的室内移动对象索引研究 [J].计算机科学,2012,39(10):177-181 [10] Yang B,Lu H,Jensen C S.Probabilistic threshold k nearestneighbor queries over moving objects in symbolic indoor space[C]∥Proceedings of the 13th International Conference on Extending Database Technology.ACM,2010:335-346 [11] Korn F,Muthukrishnan S.Influence sets based on reverse nearest neighbor queries[J].ACM SIGMOD Record,2000,29(2):201-212 [12] Stanoi I,Agrawal D,El Abbadi A.Reverse Nearest NeighborQueries for Dynamic Databases[C]∥ACM SIGMOD Workshop on Research Issues in Data Mining and Knowledge Discovery.2000:44-53 [13] Tao Y,Papadias D,Lian X.Reverse kNN search in arbitrary dimensionality[C]∥Proceedings of the Thirtieth international conference on Very large data bases-Volume 30.VLDB Endowment,2004:744-755 [14] Lian X,Chen L.Efficient processing of probabilistic reverse nearest neighbor queries over uncertain data[J].The VLDB Journal—The International Journal on Very Large Data Bases,2009,18(3):787-808 [15] Cheema M A,Lin X,Wang W,et al.Probabilistic reverse nearest neighbor queries on uncertain data[J].IEEE Transactions on Knowledge and Data Engineering,2010,22(4):550-564 [16] Bernecker T,Emrich T,Kriegel H P,et al.Efficient probabilistic reverse nearest neighbor query processing on uncertain data[J].Proceedings of the VLDB Endowment,2011,4(10):669-680 [17] Whiting E,Battat J,Teller S.Topology of urban environments[M]∥Computer-Aided Architectural Design Futures (CAADFutures) 2007.Springer Netherlands,2007:114-128 [18] Lee J.3D GIS for geo-coding human activity in micro-scale urban environments[M]∥Geographic Information Science.Springer Berlin Heidelberg,2004:162-178 [19] Jensen C S,Lu H,Yang B.Graph model based indoor tracking[C]∥Tenth International Conference on Mobile Data Management:Systems,Services and Middleware,2009(MDM’09).IEEE,2009:122-131 [20] Stoffel E P,Schoder K,Ohlbach H J.Applying hierarchicalgraphs to pedestrian indoor navigation[C]∥Proceedings of the 16th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems.ACM,2008:54 [21] Lorenz B,Ohlbach H J,Stoffel E P.A hybrid spatial model for representing indoor environments[M]∥Web and Wireless Geographical Information Systems.Springer Berlin Heidelberg,2006:102-112 |
| No related articles found! |
|
||
首页