2015/05/11 by Yaliang Li, Jing Gao, Li, Yaliang +13 · 1 citation
Computer Science · #Data Stream Mining Techniques #Databases (cs.DB) #FOS: Computer and information sciences #Mobile Crowdsensing and Crowdsourcing #Web Data Mining and Analysis
paper · pdf · doi:10.48550/arxiv.1505.02463
openalex publication_date 2015/05/11 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Thanks to information explosion, data for the objects of interest can be collected from increasingly more sources. However, for the same object, there usually exist conflicts among the collected multi-source information. To tackle this challenge, truth discovery, which integrates multi-source noisy information by estimating the reliability of each source, has emerged as a hot topic. Several truth discovery methods have been proposed for various scenarios, and they have been successfully applied in diverse application domains. In this survey, we focus on providing a comprehensive overview of truth discovery methods, and summarizing them from different aspects. We also discuss some future directions of truth discovery research. We hope that this survey will promote a better understanding of the current progress on truth discovery, and offer some guidelines on how to apply these approaches in application domains.