Truth inference in crowdsourcing: Is the problem solved?
Crowdsourcing has emerged as a novel problem-solving paradigm, which facilitates
addressing problems that are hard for computers, eg, entity resolution and sentiment …
addressing problems that are hard for computers, eg, entity resolution and sentiment …
A disaster response system based on human-agent collectives
Major natural or man-made disasters such as Hurricane Katrina or the 9/11 terror attacks
pose significant challenges for emergency responders. First, they have to develop an …
pose significant challenges for emergency responders. First, they have to develop an …
[HTML][HTML] An investigation of crowdsourcing methods in enhancing the machine learning approach for detecting online recruitment fraud
K Nanath, L Olney - International Journal of Information Management Data …, 2023 - Elsevier
Misinformation on the web has become a problem of significant impact in an information-
driven society. Persistent and large volumes of fake content are being injected, and hence …
driven society. Persistent and large volumes of fake content are being injected, and hence …
Content analysis by the crowd: Assessing the usability of crowdsourcing for coding latent constructs
Crowdsourcing platforms are commonly used for research in the humanities, social sciences
and informatics, including the use of crowdworkers to annotate textual material or visuals …
and informatics, including the use of crowdworkers to annotate textual material or visuals …
Finding convincing arguments using scalable Bayesian preference learning
E Simpson, I Gurevych - Transactions of the Association for …, 2018 - direct.mit.edu
We introduce a scalable Bayesian preference learning method for identifying convincing
arguments in the absence of gold-standard ratings or rankings. In contrast to previous work …
arguments in the absence of gold-standard ratings or rankings. In contrast to previous work …
An introduction to hybrid human-machine information systems
Abstract Hybrid Human-Machine Information Systems leverage novel architectures that
make systematic use of Human Computation by means of crowdsourcing. These …
make systematic use of Human Computation by means of crowdsourcing. These …
Predicting humorousness and metaphor novelty with Gaussian process preference learning
The inability to quantify key aspects of creative language is a frequent obstacle to natural
language understanding. To address this, we introduce novel tasks for evaluating the …
language understanding. To address this, we introduce novel tasks for evaluating the …
Inference aided reinforcement learning for incentive mechanism design in crowdsourcing
Incentive mechanisms for crowdsourcing are designed to incentivize financially self-
interested workers to generate and report high-quality labels. Existing mechanisms are often …
interested workers to generate and report high-quality labels. Existing mechanisms are often …
Time-sensitive bayesian information aggregation for crowdsourcing systems
Many aspects of the design of efficient crowdsourcing processes, such as defining worker's
bonuses, fair prices and time limits of the tasks, involve knowledge of the likely duration of …
bonuses, fair prices and time limits of the tasks, involve knowledge of the likely duration of …
Crowdsourcing for search engines: perspectives and challenges
M Moradi - International Journal of Crowd Science, 2019 - ieeexplore.ieee.org
Purpose–As a relatively new computing paradigm, crowdsourcing has gained enormous
attention in the recent decade. Its compliance with the Web 2.0 principles, also, puts forward …
attention in the recent decade. Its compliance with the Web 2.0 principles, also, puts forward …