Traditional approaches for digitizing natural history collections, which include both imaging and metadata capture, are both labour- and time-intensive. Mass-digitization can only be completed if the resource-intensive steps, such as specimen selection and databasing of associated information, are minimized. Digitization of larger collections should employ an "industrial" approach, using the pr...

Cities have long been considered as complex entities with nonlinear and dynamic properties. Pervasive urban sensing and crowd sourcing have become prevailing technologies that enhance the interplay between the cyber space and the physical world. In this paper, a spectral graph based manifold learning method is proposed to alleviate the impact of noisy, sparse and high-dimensional dataset. Corre...

In this paper we describe a data-driven interactive storytelling system similar to previous work by Gordon & Swanson. We addresses some of the problems of their system, by combining information retrieval, machine learning and natural language processing. To evaluate our system, we leverage emerging crowd-sourcing communities to collect orders of magnitude more data and show statistical improvem...

The structural and seismic fragility assessment of minor historical centers the Inner Peripheries Italy is a key phase preservation process cultural features portion Italian building stock, whose reuse crucial for reversal shrinking trends stimulation population growth. In this framework, opportunities offered by digital crowd-sourcing technologies with respect to performing probabilistic safet...

CROWDSOURCING Crowdsourcing is the practice of obtaining needed ideas, services, or content by requesting contributions from a large group of people. Amazon Mechanical Turk is a web marketplace for crowdsourcing microtasks, such as answering surveys and image tagging. We explored the limits of crowdsourcing by using Mechanical Turk for a more complicated task: analysis and creation of wind simu...