Skip to content

Research at St Andrews

Truth discovery in crowdsourced detection of spatial events

Research output: Contribution to journalArticle

Author(s)

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

School/Research organisations

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 mobile crowdsourcing is truth discovery, i.e., to discover true events from diverse and noisy participants' reports. This 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 truth discovery. In this paper, we propose two new unsupervised models, i.e., Truth finder for Spatial Events (TSE) and Personalized Truth finder for Spatial Events (PTSE), to tackle this problem. In TSE, we model location popularity, location visit indicators, truths of events, and three-way participant reliability in a unified framework. In PTSE, we further model personal location visit tendencies. These proposed models are capable of effectively handling various types of uncertainties and automatically discovering truths without any supervision or location tracking. Experimental results on both real-world and synthetic datasets demonstrate that our proposed models outperform existing state-of-the-art truth discovery approaches in the mobile crowdsourcing environment.
Close

Details

Original languageEnglish
Pages (from-to)1047-1060
Number of pages14
JournalIEEE Transactions on Knowledge and Data Engineering
Volume28
Issue number4
Early online date3 Dec 2015
DOIs
Publication statusPublished - 1 Apr 2016

    Research areas

  • Mobile crowdsourcing, Truth discovery, Probabilistic graphical models

Discover related content
Find related publications, people, projects and more using interactive charts.

View graph of relations

Related by author

  1. On natural language generation of formal argumentation

    Cerutti, F., Toniolo, A. & Norman, T. J., 27 Dec 2019, Proceedings of the 3rd Workshop on Advances In Argumentation In Artificial Intelligence co-located with the 18th International Conference of the Italian Association for Artificial Intelligence (AI*IA 2019): Rende, Italy, November 19-22, 2019. Santini, F. & Toniolo, A. (eds.). Sun SITE Central Europe, p. 15-29 15 p. (CEUR Workshop Proceedings; vol. 2528).

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

  2. Dialectical models of deliberation, problem solving and decision making

    Walton, D., Toniolo, A. & Norman, T. J., 13 Sep 2019, In : Argumentation. First Online

    Research output: Contribution to journalArticle

  3. Deb8: a tool for collaborative analysis of video

    Carneiro, G., Nacenta, M., Toniolo, A., Mendez, G. & Quigley, A. J., 4 Jun 2019, Proceedings of the 2019 ACM International Conference on Interactive Experiences for TV and Online Video (TVX '19). ACM, p. 47-58

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

  4. Deb8: collaborative fact checking

    Carneiro, G., Nacenta, M., Toniolo, A., Mendez, G. G. & Quigley, A. J., 5 May 2019.

    Research output: Contribution to conferencePaper

  5. A tool to highlight weaknesses and strengthen cases: CISpaces.org

    Cerutti, F., Norman, T. J. & Toniolo, A., 12 Dec 2018, Legal Knowledge and Information: JURIX 2018: The Thirty-first Annual Conference. Palmirani, M. (ed.). IOS Press, p. 186-189 4 p. (Frontiers in Artificial Intelligence and Applications; vol. 313).

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

Related by journal

  1. Towards real-time, country-level location classification of worldwide tweets

    Zubiaga, A., Voss, A., Procter, R., Liakata, M., Wang, B. & Tsakalidis, A., Sep 2017, In : IEEE Transactions on Knowledge and Data Engineering. 29, 9, p. 2053-2066 14 p.

    Research output: Contribution to journalArticle

  2. Aggregating crowdsourced quantitative claims: additive and multiplicative models

    Ouyang, R. W., Kaplan, L. M., Toniolo, A., Srivastava, M. & Norman, T. J., 1 Jul 2016, In : IEEE Transactions on Knowledge and Data Engineering. 28, 7, p. 1621-1634 14 p.

    Research output: Contribution to journalArticle

  3. Development of a Software Engineering Ontology for Multisite Software Development

    Wongthongtham, P., Chang, E., Dillon, T. & Sommerville, I., Aug 2009, In : IEEE Transactions on Knowledge and Data Engineering. 21, 8, p. 1205-1217 13 p.

    Research output: Contribution to journalArticle

Related by journal

  1. IEEE Transactions on Knowledge and Data Engineering (Journal)

    William Vlcek (Reviewer)

    2014

    Activity: Publication peer-review and editorial work typesPeer review of manuscripts

ID: 247864541

Top