Abstract
Given a point q, a reverse k nearest neighbor (RkNN) query retrieves all the data points that have q as one of their k nearest neighbors. Despite significant progress on this problem, there is a research gap in finding RkNNs not just for an object, but for a given range, which is a natural extension of the problem. Motivated by this, we develop algorithms for exact processing of range-based RkNN with arbitrary values of k on dynamic datasets, which retrieve all the data points that have any position in the given query range R as one of their k nearest neighbors. The experimental results demonstrate the efficiency and the accuracy of our proposed optimizations and algorithms.
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Zhong, Z., Lin, X., He, L., Yang, Y. (2018). Answering Range-Based Reverse kNN Queries. In: Cai, Y., Ishikawa, Y., Xu, J. (eds) Web and Big Data. APWeb-WAIM 2018. Lecture Notes in Computer Science(), vol 10988. Springer, Cham. https://doi.org/10.1007/978-3-319-96893-3_28
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DOI: https://doi.org/10.1007/978-3-319-96893-3_28
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