Progressive and selective merge: computing top-k with ad-hoc ranking functions

@inproceedings{Xin2007ProgressiveAS,
  title={Progressive and selective merge: computing top-k with ad-hoc ranking functions},
  author={Dong Xin and Jiawei Han and Kevin Chen-Chuan Chang},
  booktitle={SIGMOD Conference},
  year={2007}
}
The family of threshold algorithm (ie, TA) has been widely studied for efficiently computing top-k queries. TA uses a sort-merge framework that assumes data lists are pre-sorted, and the ranking functions are monotone. However, in many database applications, attribute values are indexed by tree-structured indices (eg, B-tree, R-tree), and the ranking functions are not necessarily monotone. To answer top-k queries with ad-hoc ranking functions, this paper studies anindex-merge paradigm that… CONTINUE READING
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