Crowdsourcing & Human-in-the-Loop
Quality-aware human-in-the-loop systems for data collection, processing, and analysis in data-intensive applications.
Large-scale data management cannot rely on machines alone. Human judgment is essential for handling ambiguity, ensuring quality, and interpreting domain-specific context. My research develops human-in-the-loop frameworks that integrate crowd contributions intelligently at each stage of the data pipeline.
Data collection and quality
I have developed models and tools for evaluating and improving data quality in crowdsourced settings, including crowd-based annotation tasks and quality metrics that account for worker expertise and bias (Bozzon et al., 2013) (Bozzon et al., 2015).
Crowdsourcing platforms and patterns
Early work at Politecnico di Milano produced pattern-based specifications for crowdsourcing applications (Bozzon et al., 2014), community-based crowdsourcing models (Brambilla et al., 2014), and adaptive platform designs (Brambilla et al., 2015).
Applications
Human-in-the-loop methods have been applied across several domains:
- Music transcription — microtask crowdsourcing for music score error detection (Samiotis et al., 2020)
- Energy consumption — user-generated content analysis for smart city energy behavior (Mauri et al., 2018) (de Kok et al., 2019)
- Social research — complementing studies on vulnerable youth with social media data (Mauri et al., 2021)
- Privacy — human-in-the-loop approaches to image privacy preservation (Mauri & Bozzon, 2021)
References
2021
- CHItalyComplementing Studies on Vulnerable Youths with Reddit DataIn 14th Biannual Conference of the Italian SIGCHI Chapter (CHItaly), 2021
- IIRTowards a Human in the Loop Approach to Preserve Privacy in ImagesIn 11th Italian Information Retrieval Workshop (IIR), 2021
2020
- ISMIRMicrotask Crowdsourcing for Music Score Transcriptions: an Experiment with Error DetectionIn International Society for Music Information Retrieval Conference (ISMIR), 2020
2019
- EnergiesAutomatic Processing of User-Generated Content for the Description of Energy-Consuming Activities at Individual and Group LevelEnergies, 2019
2018
- WWW
2015
- JWEDesigning Complex Crowdsourcing Applications Covering Multiple Platforms and TasksJournal of Web Engineering, 2015
- IEEE IC
2014
- ICWEPattern-based Specification of Crowdsourcing ApplicationsIn International Conference on Web Engineering (ICWE), 2014
- WWWCommunity-based CrowdsourcingIn Proceedings of the 23rd International Conference on World Wide Web Companion (WWW), 2014
2013
- WWWReactive crowdsourcingIn Proceedings of the 22nd International Conference on World Wide Web (WWW), 2013