Abstract
Similarity search is a common computational task in many applications. Distance-based indexing techniques are proposed to enhance performance for similarity search in metric space. In this paper, we propose an enhanced search algorithm for Vantage Point Tree with an inclusion rule based on an upper bound on distances between the query item and objects in database. In a range search task, objects which satisfy the inclusion rule also satisfy the range query, which means we can return them as results without distance calculations. We obtain experimental results showing that our enhanced algorithm outperforms the algorithm without inclusion rule significantly when the query radius is large.
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© 2015 Springer International Publishing Switzerland
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Zeng, G., Li, Q., Jia, H., Li, X., Cai, Y., Mao, R. (2015). An Inclusion Rule for Vantage Point Tree Range Query Processing. In: Zu, Q., Hu, B., Gu, N., Seng, S. (eds) Human Centered Computing. HCC 2014. Lecture Notes in Computer Science(), vol 8944. Springer, Cham. https://doi.org/10.1007/978-3-319-15554-8_68
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DOI: https://doi.org/10.1007/978-3-319-15554-8_68
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