Towards Confidence in the Truth: A Bootstrapping based Truth Discovery Approach

  title={Towards Confidence in the Truth: A Bootstrapping based Truth Discovery Approach},
  author={Houping Xiao and Jing Gao and Qi Li and Fenglong Ma and Lu Su and Yunlong Feng and Aidong Zhang},
The demand for automatic extraction of true information (i.e., truths) from conflicting multi-source data has soared recently. A variety of truth discovery methods have witnessed great successes via jointly estimating source reliability and truths. All existing truth discovery methods focus on providing a point estimator for each object's truth, but in many real-world applications, confidence interval estimation of truths is more desirable, since confidence interval contains richer information… CONTINUE READING
Highly Cited
This paper has 25 citations. REVIEW CITATIONS

From This Paper

Figures, tables, and topics from this paper.


Publications citing this paper.
Showing 1-10 of 18 extracted citations

Effective Integration of Geotagged, Ancilliary Longitudinal Survey Datasets to Improve Adulthood Obesity Predictive Models

2018 17th IEEE International Conference On Trust, Security And Privacy In Computing And Communications/ 12th IEEE International Conference On Big Data Science And Engineering (TrustCom/BigDataSE) • 2018
View 1 Excerpt

Constraint-aware dynamic truth discovery in big data social media sensing

2017 IEEE International Conference on Big Data (Big Data) • 2017
View 2 Excerpts

Discovering Truths from Distributed Data

2017 IEEE International Conference on Data Mining (ICDM) • 2017
View 6 Excerpts


Publications referenced by this paper.

Similar Papers

Loading similar papers…