We introduce our work on the use of prediction markets as a tool for mining knowledge from within an enterprise (i.e., Nokia Corporation). Various companies – including Google, HP, and Yahoo – have experimented with internal prediction market services, testing its utility for tapping knowledge distributed and nascent within their organization. We are also exploring the use of this tool for capt...

This paper details our work towards designing a system for crowd-sourcing responses on thermal comfort in naturally ventilated office buildings. We provide preliminary qualitative findings on the deployment of this system. Specifically, we explore the different human factors that led to our system being used as something akin to a digital complaints box and how we intend to adapt and leverage t...

In this paper we address the issue of optimizing the actual social photo retrieval technology in terms of users’ requirements. Typical users are interested in taking possession of accurately relevant-to-the-query and non-redundant images so they can build a correct exhaustive perception over the query. We propose to tackle this issue by combining two approaches previously considered nonoverlapp...

This article compares the results of building damage detection based on Crowd Sourced (CS) data, image processing of remotely sensed (RS) data and predictive modelling with institutional spatial data (Spatial Data Infrastructure SDI). In particular, it focuses on the contribution of Crowd Sourcing to detecting postearthquake building damages, while also considering the integration of Crowd Sour...

A discriminative model is presented for crowd-sourcing the annotation of news stories to produce a structured dataset about incidents involving militarized disputes between nation-states. We used a question tree to gather partially redundant data from each crowd worker. A lattice of Bayesian Networks was then applied to error correct the individual worker annotations, the results of which were ...

We present early results on crowd sourcing translations in an enterprise setting. We show that several weak translators can together converge to translation quality higher than individually plausible. We share learning about post editing of translations and the effort perceived by the crowd. A key observation is that a protocol “machine-human-human” that utilizes two-hop post editing can provid...

In this paper, we consider the problem of incentive mechanism design for smart-phone crowd-sourcing. Each user participating in crowd-sourcing submits a set of tasks it can accomplish and its corresponding bid. The platform then selects the users and their payments to maximize its utility while ensuring truthfulness, individual rationality, profitability, and polynomial algorithm complexity. Bo...

Although several itinerary recommender systems have been proposed in the literature, they usually don’t allow users to further improve the available set of tourist attractions by submitting information in a collaborative manner. In this paper we present a collaborative itinerary recommender system that relies on crowd sourcing to both expand and maintain current the dataset of attractions. The ...

Interactive narrative (IN) has increasingly been used for social skill training. However, extensive content creation is needed to provide learners with flexibility to replay scenarios with sufficient variety to achieve proficiency. Such flexibility requires considerable content creation appropriate for social skills training. The goal of our work is to address these issues through developing a ...