We show how full-text search based on inverted indices can be accelerated by clustering the documents without losing results (SeCluD – Search with Clustered Documents). We develop a fast multilevel clustering algorithm that uses query cost of conjunctive queries as an objective function. Depending on the inputs we get up to four times faster than non-clustered search. The resulting clusters are also useful for data compression and for distributing the work over many machines.
CITATION STYLE
Dimond, J., & Sanders, P. (2015). Faster exact search using document clustering. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 9309, pp. 1–12). Springer Verlag. https://doi.org/10.1007/978-3-319-23826-5_1
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