Truth discovery in crowdsourced detection of spatial events

Robin Wentao Ouyang, Mani Srivastava, Alice Toniolo, Timothy J. Norman

Research output: Chapter in Book/Report/Conference proceedingConference contribution

19 Citations (Scopus)

Abstract

The ubiquity of smartphones has led to the emergence of mobile crowdsourcing tasks such as the detection of spatial events when smartphone users move around in their daily lives. However, the credibility of those detected events can be negatively impacted by unreliable participants with low-quality data. Consequently, a major challenge in quality control is to discover true events from diverse and noisy participants' reports. This truth discovery problem is uniquely distinct from its online counterpart in that it involves uncertainties in both participants' mobility and reliability. Decoupling these two types of uncertainties through location tracking will raise severe privacy and energy issues, whereas simply ignoring missing reports or treating them as negative reports will significantly degrade the accuracy of the discovered truth. In this paper, we propose a new method to tackle this truth discovery problem through principled probabilistic modeling. In particular, we integrate the modeling of location popularity, location visit indicators, truth of events and three-way participant reliability in a unified framework. The proposed model is thus capable of efficiently handling various types of uncertainties and automatically discovering truth without any supervision or the need of location tracking. Experimental results demonstrate that our proposed method outperforms existing state-of-the-art truth discovery approaches in the mobile crowdsourcing environment.

Original languageEnglish
Title of host publicationCIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management
PublisherACM
Pages461-470
Number of pages10
ISBN (Electronic)9781450325981
DOIs
Publication statusPublished - 3 Nov 2014
Event23rd ACM International Conference on Information and Knowledge Management, CIKM 2014 - Shanghai, China
Duration: 3 Nov 20147 Nov 2014

Publication series

NameCIKM 2014 - Proceedings of the 2014 ACM International Conference on Information and Knowledge Management

Conference

Conference23rd ACM International Conference on Information and Knowledge Management, CIKM 2014
Country/TerritoryChina
CityShanghai
Period3/11/147/11/14

Keywords

  • Graphical models
  • Mobile crowdsourcing
  • Quality control

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