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Hierarchical Graph Traversal for Aggregate k Nearest Neighbors Search in Road Networks (Extended Abstract)

Tenindra Abeywickrama, Muhammad Aamir Cheema, Sabine Storandt
2021 Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence   unpublished
In this paper, we study a natural extension of the kNN query for multiple agents, namely, the Aggregate k Nearest Neighbors (AkNN) query.  ...  A k nearest neighbors (kNN) query finds k closest points-of-interest (POIs) from an agent's location.  ...  An AkNN query returns k POIs with the smallest aggregate distances. Yiu et al. [Yiu et al., 2005] solve the AkNN query using a hierarchical search on the road network.  ... 
doi:10.24963/ijcai.2021/640 fatcat:ms2hrns2jja7vb2to75v2xxltq

Fast object search on road networks

Ken C. K. Lee, Wang-Chien Lee, Baihua Zheng
2009 Proceedings of the 12th International Conference on Extending Database Technology Advances in Database Technology - EDBT '09  
In ROAD, a large road network is organized as a hierarchy of interconnected regional sub-networks (called Rnets) augmented with 1) shortcuts for accelerating network traversals; and 2) object abstracts  ...  By exploiting search space pruning technique and providing a dynamic object mapping mechanism, ROAD is very efficient and flexible for various types of queries, namely, range search and nearest neighbor  ...  SEARCH ALGORITHMS While ROAD is designed to support different types of LD-SQs, in this paper, we focus on k-nearest neighbor (kNN) queries and range queries.  ... 
doi:10.1145/1516360.1516476 dblp:conf/edbt/LeeLZ09 fatcat:ibihsetr55cz3b3uptzxg3mmb4

Natural Variability [chapter]

2017 Encyclopedia of GIS  
In: Proceedings of the ACM SIG-MOD international conference on management of data, San Jose, pp 71-79 Nearest Neighbor Search k-NN Search in Time-Dependent Road Networks Trip Planning Queries in Road Network  ...  segment (white), and (iii) depending on the N Nearest Neighbor Queries in Network Databases, Fig. 3 Graph modeling of the road network (a) a road network, (b) the modeling graph application, additional  ...  Cartography principles provide the fundamental methods in separating computing objects into pieces to be calculated on different computers and abstracting computing objects into different levels to facilitate  ... 
doi:10.1007/978-3-319-17885-1_101534 fatcat:aj3jjedtq5ezbpoakmsuxw7pba

Memory-Efficient RkNN Retrieval by Nonlinear k-Distance Approximation [article]

Sandra Obermeier, Max Berrendorf, Peer Kröger
2020 arXiv   pre-print
The reverse k-nearest neighbor (RkNN) query is an established query type with various applications reaching from identifying highly influential objects over incrementally updating kNN graphs to optimizing  ...  In this work, we investigate this assumption and uncover that it is violated in regions of changing density, which we show are typical for real-life datasets.  ...  Abstract-The reverse k-nearest neighbor (RkNN) query is an established query type with various applications reaching from identifying highly influential objects over incrementally updating kNN graphs to  ... 
arXiv:2011.01773v1 fatcat:vbgf2ksczvhxvjtdwasczhrlrq

k-Nearest Keyword Search in RDF Graphs

Xiang Lian, Eugenio D. Hoyos, Artem Chebotko, Bin Fu, Christine Reilly
2013 Social Science Research Network  
Inspired by this problem, in this paper, we propose and tackle a novel and important query type, namely k-nearest keyword (k-NK) query, over a large RDF graph.  ...  To efficiently answer k-NK queries, we design effective pruning methods for RDF graphs both with and without schema, which can greatly reduce the query search space.  ...  [24] studied the nearest neighbor search in a spatial road network (planar graph), which utilizes the relationship between spatial distance and network distance to enable the pruning.  ... 
doi:10.2139/ssrn.3199072 fatcat:pvnqskolxzdiracp5dlf25wd3y

Filtering [chapter]

2017 Encyclopedia of GIS  
Sections "Depth-First k-Nearest Neighbor Method" and "Best-First k-Nearest Neighbor Method" describe the depth-first and best-first This work was supported in part by the National Science Foundation under  ...  from having to know the value of k in advance, and, more importantly, there is no need to restart the k-nearest neighbor search process when k increases as we can simply resume/continue the search for  ...  Finding k-Nearest Neighbors for Non-point Objects The incremental implementation of the best-first nearest neighbor method in section "Finding the k-Nearest Neighbors in Incremental Order" can only handle  ... 
doi:10.1007/978-3-319-17885-1_100413 fatcat:bl66hlinfzaqjopolsm2phk4kq

Approximate Shortest Distance Computing: A Query-Dependent Local Landmark Scheme

Miao Qiao, Hong Cheng, Lijun Chang, Jeffrey Xu Yu
2014 IEEE Transactions on Knowledge and Data Engineering  
Two optimization techniques on graph compression and graph online search are also proposed, with the goal of further reducing index size and improving query accuracy.  ...  Our experimental results on large-scale social networks and road networks demonstrate that the local landmark scheme reduces the shortest distance estimation error significantly when compared with global  ...  [25] build a shortest path quadtree to support k-nearest neighbor queries in spatial networks.  ... 
doi:10.1109/tkde.2012.253 fatcat:msdm5edmnnaqrli5vh6my4txsm

A framework for predicting trajectories using global and local information

William Groves, Ernesto Nunes, Maria Gini
2014 Proceedings of the 11th ACM Conference on Computing Frontiers - CF '14  
We propose a novel framework for predicting the paths of vehicles that move on a road network. The framework leverages global and local patterns in spatio-temporal data.  ...  graph data, and (3) a component that predicts the subsequent path of an in-progress trajectory.  ...  [12] use a landmark graph to build relationships between the road segments the taxis traverse frequently.  ... 
doi:10.1145/2597917.2597934 dblp:conf/cf/GrovesNG14 fatcat:bxdkmgsqpzby7lgn6jqnunjbvu

Recent Advances in Graph Partitioning [chapter]

Aydın Buluç, Henning Meyerhenke, Ilya Safro, Peter Sanders, Christian Schulz
2016 Lecture Notes in Computer Science  
We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions.  ...  Acknowledgements We express our gratitude to Bruce Hendrickson, Dominique LaSalle, and George Karypis for many valuable comments on a preliminary draft of the manuscript.  ...  This method gives performance guarantees for planar graphs, k-nearest neighbor graphs, and other well-behaved graphs.  ... 
doi:10.1007/978-3-319-49487-6_4 fatcat:4zamxcmgvfbaxndjgxv6jog6km

Recent Advances in Graph Partitioning [article]

Aydin Buluc, Henning Meyerhenke, Ilya Safro, Peter Sanders, Christian Schulz
2015 arXiv   pre-print
We survey recent trends in practical algorithms for balanced graph partitioning together with applications and future research directions.  ...  Acknowledgements We express our gratitude to Bruce Hendrickson, Dominique LaSalle, and George Karypis for many valuable comments on a preliminary draft of the manuscript.  ...  This method gives performance guarantees for planar graphs, k-nearest neighbor graphs, and other "well-behaved" graphs.  ... 
arXiv:1311.3144v3 fatcat:zmvhlkh7ynbzvm353fv22f2gnq

Scalable Pattern Matching in Metadata Graphs via Constraint Checking [article]

Tahsin Reza, Hassan Halawa, Matei Ripeanu, Geoffrey Sanders, Roger Pearce
2020 arXiv   pre-print
Pattern matching is a fundamental tool for answering complex graph queries.  ...  The key intuition is that each vertex or edge participating in a match has to meet a set of constrains implicitly specified by the search template.  ...  , road network graph, Road USA.  ... 
arXiv:1912.08453v2 fatcat:jrf3hcy6bnbcff6z256yefjowu

Weighted k-Nearest Neighbor Adaptations to Spare Part Prediction Business Scenario at SAP System

Eren Esgin
2020 Proceedings of the 9th International Conference on Operations Research and Enterprise Systems  
Weighted k-Nearest Neighbor Adaptations to Spare Part Prediction Business Scenario at SAP System.  ...  This paper proposes a hybrid classification model that combines C4.5, Apriori algorithms and weighted k-Nearest Neighbor (kNN) adaptations to overcome potential shortcomings observed at the corresponding  ...  (Tan, 2015) proposed the algorithm Neighbor-Weighted k-Nearest Neighbor (NWkNN), which applies a weighing strategy based on the distribution of classes.  ... 
doi:10.5220/0009103202180226 dblp:conf/icores/Esgin20 fatcat:swbm745igjhkrlmtgslnzf2vee

Location-dependent query processing

Sergio Ilarri, Eduardo Mena, Arantza Illarramendi
2010 ACM Computing Surveys  
The continuous development of wireless networks and mobile devices has motivated an intense research in mobile data services. Some of these services provide the user with context-aware information.  ...  In this article, the existing literature in the field of location-dependent query processing is reviewed.  ...  Nearest-Neighbor Queries on Static Objects with a Query Point Moving in a Road Network.  ... 
doi:10.1145/1670679.1670682 fatcat:6mlurrqvgvaapmw5pmm7sfz6n4

Sensing for Mobile Objects [chapter]

Nicholas D. Larusso, Ambuj K. Singh
2012 Managing and Mining Sensor Data  
We discuss some of the common approaches used for tracking and examine some recent work which focuses specifically on tracking vehicles using a road network.  ...  First, we cover recent advances in database systems for managing spatiotemporal data, including index structures and efficient algorithms for processing queries.  ...  For identifying nearby objects in the context of trajectory data, the continuous nearest-neighbor (CNN) query has been proposed in which a sequence of nearest neighbors are returned such that the nearest-neighbor  ... 
doi:10.1007/978-1-4614-6309-2_10 fatcat:b6xsuttztrfcnk5grrxpnged3a

Outlier Detection for Temporal Data: A Survey

Manish Gupta, Jing Gao, Charu C. Aggarwal, Jiawei Han
2014 IEEE Transactions on Knowledge and Data Engineering  
In the statistics community, outlier detection for time series data has been studied for decades.  ...  In this survey, we provide a comprehensive and structured overview of a large set of interesting outlier definitions for various forms of temporal data, novel techniques, and application scenarios in which  ...  R is anti-monotonic wrt data and R should be smooth, e.g., the distance to the k th nearest neighbor, the average distance to the k nearest neighbors, etc. Consider a point x in dataset P .  ... 
doi:10.1109/tkde.2013.184 fatcat:b6nableuvvgthlw3xxj6axabgi
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