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2016 IEEE 32nd International Conference on Data Engineering (ICDE) (2016)
Helsinki, Finland
May 16, 2016 to May 20, 2016
ISBN: 978-1-5090-2020-1
pp: 1536-1537
Hui Yan , Department of Computer and Information Science, University of Macau, China
Zhiguo Gong , Department of Computer and Information Science, University of Macau, China
Nan Zhang , Department of Computer Science, The George Washington University, USA
Tao Huang , State Key Laboratory of Computer Science & Technology Center of Software Engineering, Institute of Software, Chinese Academy of Science, China
Hua Zhong , State Key Laboratory of Computer Science & Technology Center of Software Engineering, Institute of Software, Chinese Academy of Science, China
Jun Wei , State Key Laboratory of Computer Science & Technology Center of Software Engineering, Institute of Software, Chinese Academy of Science, China
ABSTRACT
With rapidly growing popularity, Location Based Services (LBS), e.g., Google Maps, Yahoo Local, WeChat, FourSquare, etc., started offering web-based search features that resemble a kNN query interface. Specifically, for a user-specified query location q, these websites extract from the objects in their backend database the top-k nearest neighbors to q and return these k objects to the user through the web interface. Here k is often a small value like 50 or 100. For example, McDonald [1] returns the top 25 nearest restaurants for a user-specified location through its locations search webpage.
INDEX TERMS
Spatial databases, Algorithm design and analysis, Prediction algorithms, Computer science, Knowledge based systems, Google
CITATION

H. Yan, Z. Gong, N. Zhang, T. Huang, H. Zhong and J. Wei, "Crawling hidden objects with kNN queries," 2016 IEEE 32nd International Conference on Data Engineering (ICDE), Helsinki, Finland, 2016, pp. 1536-1537.
doi:10.1109/ICDE.2016.7498412
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