A sampling-based framework for crowdsourced select query with multiple predicates

  • Jianhong Feng*
  • , Huiqi Hu
  • , Xueping Weng
  • , Jianhua Feng
  • , Yongwei Wu
  • *Corresponding author for this work

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In this paper, we consider the crowdsourced select query with multiple predicates.We find that different predicates have different selectivities. An important problem is to determine a good predicate order. However it is rather hard to obtain an optimal order. To address this problem, we propose a sampling-based framework to find a high-quality order. We devise a minimum random selection method by randomly selecting the predicate sequence. Since minimum random selection randomly selects predicate permutations over predicates, which may bring large cost, we propose a filtering based algorithm to further reduce the cost. We evaluate our method using a real-world dataset. Experimental results indicate that our methods significantly reduce the monetary cost.

Original languageEnglish
Title of host publicationWeb-Age Information Management - 16th International Conference, WAIM 2015, Proceedings
EditorsYizhou Sun, Jian Li
PublisherSpringer Verlag
Pages525-529
Number of pages5
ISBN (Electronic)9783319210414
DOIs
StatePublished - 2015
Externally publishedYes
Event16th International Conference on Web-Age Information Management, WAIM 2015 - Qingdao, China
Duration: 8 Jun 201510 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9098
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference16th International Conference on Web-Age Information Management, WAIM 2015
Country/TerritoryChina
CityQingdao
Period8/06/1510/06/15

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