A Top-K Retrieval algorithm based on a decomposition of ranking functions

被引:1
|
作者
Madrid, Nicolas [1 ]
Rusnok, Pavel [2 ]
机构
[1] Univ Malaga, Dept Appl Math, Malaga, Spain
[2] Univ Ostrava, Inst Res & Applicat Fuzzy Modeling, Ostrava, Czech Republic
关键词
Top-k retrieval; Ranking functions; Preferences; Big data; QUERIES;
D O I
10.1016/j.ins.2018.09.014
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
A Top-k retrieval algorithm returns the k best answers of a query according to a given ranking. From a theoretical point of view, the solution of this query is straightforward if we do not take into consideration execution time. However, in many practical situations, execution time is a substantial issue. In such a case, the process of getting the top k in an optimal time becomes an interesting and non-trivial task. This paper presents an algorithm to retrieve the top-k associated to an arbitrary ranking function. The idea is to decompose the ranking function as a supremum of a certain set of functions where an efficient top-k retrieval procedure can be easily applied. Besides the theoretical presentation of the algorithm, the paper provides a set of experiments to validate the approach. (C) 2018 Elsevier Inc. All rights reserved.
引用
收藏
页码:136 / 153
页数:18
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