Efficiently Monitoring Top-k Pairs over Sliding Windows

被引:14
|
作者
Shen, Zhitao [1 ]
Cheema, Muhammad Aamir [1 ]
Lin, Xuemin [1 ,2 ]
Zhang, Wenjie [1 ]
Wang, Haixun [3 ]
机构
[1] Univ New S Wales, Sydney, NSW 2052, Australia
[2] East China Normal Univ, Shanghai, Peoples R China
[3] Microsoft Res Asia, Beijing, Peoples R China
来源
2012 IEEE 28TH INTERNATIONAL CONFERENCE ON DATA ENGINEERING (ICDE) | 2012年
关键词
D O I
10.1109/ICDE.2012.89
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
Top-k pairs queries have received significant attention by the research community. k-closest pairs queries, k-furthest pairs queries and their variants are among the most well studied special cases of the top-k pairs queries. In this paper, we present the first approach to answer a broad class of top-k pairs queries over sliding windows. Our framework handles multiple top-k pairs queries and each query is allowed to use a different scoring function, a different value of k and a different size of the sliding window. Although the number of possible pairs in the sliding window is quadratic to the number of objects N in the sliding window, we efficiently answer the top-k pairs query by maintaining a small subset of pairs called K-skyband which is expected to consist of O(K log(N/K)) pairs. For all the queries that use the same scoring function, we need to maintain only one K-skyband. We present efficient techniques for the K-skyband maintenance and query answering. We conduct a detailed complexity analysis and show that the expected cost of our approach is reasonably close to the lower bound cost. We experimentally verify this by comparing our approach with a specially designed supreme algorithm that assumes the existence of an oracle and meets the lower bound cost.
引用
收藏
页码:798 / 809
页数:12
相关论文
共 50 条
  • [21] Mining top-k frequent patterns over data streams sliding window
    Hui Chen
    Journal of Intelligent Information Systems, 2014, 42 : 111 - 131
  • [22] Spatio-temporal top-k term search over sliding window
    Chen, Lisi
    Shang, Shuo
    Yao, Bin
    Zheng, Kai
    WORLD WIDE WEB-INTERNET AND WEB INFORMATION SYSTEMS, 2019, 22 (05): : 1953 - 1970
  • [23] Efficiently Inferring Top-k Largest Monitoring Data Entries Based on Discrete Tensor Completion
    Tian, Jiazheng
    Xie, Kun
    Wang, Xin
    Xie, Gaogang
    Li, Kenli
    Wen, Jigang
    Zhang, Dafang
    Cao, Jiannong
    IEEE-ACM TRANSACTIONS ON NETWORKING, 2021, 29 (06) : 2737 - 2750
  • [24] Efficiently Summarizing Data Streams over Sliding Windows
    Rivetti, Nicolo
    Busnel, Yann
    Mostefaoui, Achour
    2015 IEEE 14th International Symposium on Network Computing and Applications (NCA), 2015, : 151 - 158
  • [25] Efficiently Mining Top-K High Utility Sequential Patterns
    Yin, Junfu
    Zheng, Zhigang
    Cao, Longbing
    Song, Yin
    Wei, Wei
    2013 IEEE 13TH INTERNATIONAL CONFERENCE ON DATA MINING (ICDM), 2013, : 1259 - 1264
  • [26] Sliding window top-k dominating query processing over distributed data streams
    Amagata, Daichi
    Hara, Takahiro
    Nishio, Shojiro
    DISTRIBUTED AND PARALLEL DATABASES, 2016, 34 (04) : 535 - 566
  • [27] SKYPE: Top-k Spatial-keyword Publish/Subscribe Over Sliding Window
    Wang, Xiang
    Zhang, Ying
    Zhang, Wenjie
    Lin, Xuemin
    Huang, Zengfeng
    PROCEEDINGS OF THE VLDB ENDOWMENT, 2016, 9 (07): : 588 - 599
  • [28] Sliding window top-k dominating query processing over distributed data streams
    Daichi Amagata
    Takahiro Hara
    Shojiro Nishio
    Distributed and Parallel Databases, 2016, 34 : 535 - 566
  • [29] Efficiently Approximating Top-k Sequential Patterns in Transactional Graphs
    Lei, Mingtao
    Zhang, Xi
    Yang, Jincui
    Fang, Binxing
    IEEE ACCESS, 2019, 7 : 62817 - 62832
  • [30] A practical approach for efficiently answering top-k relational queries
    Ayanso, Anteneh
    Goes, Paulo B.
    Mehta, Kumar
    DECISION SUPPORT SYSTEMS, 2007, 44 (01) : 326 - 349