Crowdsourcing triggers rapid, reliable earthquake locations

Absolute Earthquake Locations with Differential Data

Not withstanding the commonly-held wisdom that “you can’t determine the absolute location of earthquakes using the double-difference method”, you can. We present a way of visualizing double-difference data, and use it to show how differential arrival time data can, in principle, be used to determine the absolute locations of earthquakes. We then analyze the differential form of Geiger’s Method,...

Iterative Learning for Reliable Crowdsourcing Systems

Iterative Learning for Reliable Crowdsourcing Systems Citation

Crowdsourcing systems, in which tasks are electronically distributed to numerous “information piece-workers”, have emerged as an effective paradigm for humanpowered solving of large scale problems in domains such as image classification, data entry, optical character recognition, recommendation, and proofreading. Because these low-paid workers can be unreliable, nearly all crowdsourcers must de...

Iterative Learning for Reliable Crowdsourcing Systems

Crowdsourcing systems, in which tasks are electronically distributed to numerous “information piece-workers”, have emerged as an effective paradigm for humanpowered solving of large scale problems in domains such as image classification, data entry, optical character recognition, recommendation, and proofreading. Because these low-paid workers can be unreliable, nearly all crowdsourcers must de...

Reliable Task Design for Descriptive Crowdsourcing

Crowdsourcing offers a valuable method to improve information retrieval indexing by using humans to improve the indexable data about documents or entities. Human contributions open the door to latent information, subjective judgments, and other encoding of difficult to extract data. However, such contributions are also subject to variance from the inconsistencies of human interpretation. The pr...