Crowdsourced ranking algorithms ask the crowd to compare the objects and infer the full
ranking based on the crowdsourced pairwise comparison results. In this paper, we consider …

Crowdsourcing services make it possible to collect huge amount of annotations from less
trained crowd workers in an inexpensive and efficient manner. However, unlike making …

Many applications supported by the crowdsourcing are subject to delay constraints. The
timely outcome returned with a better partial fulfillment is preferable to the full completion …

Rank aggregation based on pairwise comparisons over a set of items has a wide range of
applications. Although considerable research has been devoted to the development of rank …

Inferring a gold-standard ranking over a set of objects, such as documents or images, is a
key task to build test collections for various applications like Web search and recommender …

Crowdsourcing has been considered as one of the most promising services in recent years.
More and more crowdsourcing platforms allocate tasks over the social network due to its …

Driven by the dramatic growth of data both in terms of the size and sources, learning from
heterogeneous data is emerging as an important research direction for many real …

A common feature among many crowdsourcing applications is to decompose the huge or
complex tasks into some small sub-ones, which require some users with different skills to …

The paper tackles the problem of finding the correct solution to a set of binary choice
questions or labeling tasks, by adaptively assigning them to workers in a crowdsourcing …

Crowdsourcing is a very popular model on the Internet. It is a common task assignment
method to assign multiple tasks according to workers' subjective preferences in …