Group Nearest Neighbor Queries
ICDE '04 Proceedings of the 20th International Conference on Data Engineering
Aggregate nearest neighbor queries in spatial databases
ACM Transactions on Database Systems (TODS)
Two ellipse-based pruning methods for group nearest neighbor queries
Proceedings of the 13th annual ACM international workshop on Geographic information systems
Keyword Search on Spatial Databases
ICDE '08 Proceedings of the 2008 IEEE 24th International Conference on Data Engineering
Keyword Search in Spatial Databases: Towards Searching by Document
ICDE '09 Proceedings of the 2009 IEEE International Conference on Data Engineering
Efficient retrieval of the top-k most relevant spatial web objects
Proceedings of the VLDB Endowment
IR-Tree: An Efficient Index for Geographic Document Search
IEEE Transactions on Knowledge and Data Engineering
Collective spatial keyword querying
Proceedings of the 2011 ACM SIGMOD International Conference on Management of data
Efficient continuously moving top-k spatial keyword query processing
ICDE '11 Proceedings of the 2011 IEEE 27th International Conference on Data Engineering
Efficient processing of top-k spatial keyword queries
SSTD'11 Proceedings of the 12th international conference on Advances in spatial and temporal databases
IEEE Transactions on Knowledge and Data Engineering
Multi-approximate-keyword routing in GIS data
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
On Group Nearest Group Query Processing
IEEE Transactions on Knowledge and Data Engineering
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Due to the proliferation of Location-Based Service and popularity of online geo-tagged web pages, spatial keyword search has attracted significant attention from both academic and industrial communities. In this paper, we study the problem of finding the nearest aggregate point from multiple query points travelling through a set objects described by a given set of keywords, as well as the optimal routes from the query points to the aggregate point. This problem is defined as the Aggregate Keyword Routing (AKR) Query. We devise an exact algorithm to AKR query based on ellipse pruning. Next we propose an efficient approximate algorithm for AKR: Center Based Assignment (CBA). The performance of the proposed algorithms are evaluated with real data, the results demonstrate the efficiency and the effectiveness.