We investigate the problem of large-scale mobile crowdtasking, where a large pool of citizen crowd-workers are used to perform a variety of location-specific urban logistics tasks. Current approaches to such mobile crowd-tasking are very decentralized: a crowd-tasking platform usually provides each worker a set of available tasks close to the worker’s current location; each worker then independ...

We propose an approach for supporting attribute exploration by web information retrieval, in particular by posing appropriate queries to search engines, crowd sourcing systems, and the linked open data cloud. We discuss underlying general assumptions for this to work and the degree to which these can be taken for granted.

For some emergency situations an effective response can be reliant on sensor data (e.g. river level, traffic flow, weather conditions) to provide situation awareness, in order to help authorities make informed decisions. Gathering data in a traditional approach, i.e. using precise physical sensors, is a highly expensive task, involving procurement, installation and maintenance of a number of se...

This paper describes an on-going project investigating the use of crowdsourcing in policy consultation. We see this as particularly useful in the early consultation stages (e.g. White Paper) when the opinions of the public are sought to determine policy objectives. The project involves a number of discrete stages: thus far we have looked especially at question design, the generation of suitable...

Crowdsourcing has increasingly become a recognized sourcing mechanism for problem-solving in organizations by outsourcing the problem to an undefined entity or the ‘crowd’. While the phenomenon of crowdsourcing is not new, it has gained considerable attention in practice due to new crowdsourcing opportunities that have been enabled by new social networking and web 2.0 technologies. While crowds...

This paper investigates the feasibility of using crowd-sourcing services for the human assessment of machine translation quality of English and Japanese translation tasks. Nonexpert graders are hired in order to carry out a ranking-based MT evaluation of utterances taken from the domain of travel conversations. Besides a thorough analysis of the obtained non-expert grading results, data quality...

Skyline queries are a well-known technique for explorative retrieval, multi-objective optimization problems, and personalization tasks in databases. They are widely acclaimed for their intuitive query formulation mechanisms. However, when operating on incomplete datasets, skyline query processing is severely hampered and often has to resort to error-prone heuristics. Unfortunately, incomplete d...

Crowd-sourcing is a recent framework in which human intelligence tasks are outsourced to a crowd of unknown people (”workers”) as an open call (e.g., on Amazon’s Mechanical Turk). Crowd-sourcing has become immensely popular with hoards of employers (”requesters”), who use it to solve a wide variety of jobs, such as dictation transcription, content screening, etc. In order to achieve quality res...

We study the problems of max/top-k and clustering when the comparison operations may be performed by oracles whose answer may be erroneous. Comparisons may either be of type or of value: given two data elements, the answer to a type comparison is “yes” if the elements have the same type and therefore belong to the same group (cluster); the answer to a value comparison orders the two data elemen...