Abstract
Supporting top-k document retrieval queries on general text databases, that is, finding the k documents where a given pattern occurs most frequently, has become a topic of interest with practical applications. While the problem has been solved in optimal time and linear space, the actual space usage is a serious concern. In this paper we study various reduced-space structures that support top-k retrieval and propose new alternatives. Our experimental results show that our novel structures and algorithms dominate almost all the space/time tradeoff.
Partially funded by Fondecyt Grant 1-110066, Chile.
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Navarro, G., Valenzuela, D. (2012). Space-Efficient Top-k Document Retrieval. In: Klasing, R. (eds) Experimental Algorithms. SEA 2012. Lecture Notes in Computer Science, vol 7276. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-30850-5_27
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DOI: https://doi.org/10.1007/978-3-642-30850-5_27
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