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Crime prediction plays a crucial role in addressing crime, violence, conflict and insecurity in cities to promote good governance, appropriate urban planning and management. Plenty efforts have been made on developing crime prediction models by leveraging demographic data, but they failed to capture the dynamic nature of crimes in urban. Recently, with the development of new techniques for collecting...
In recent years, companies and non-profit organizations are increasingly leveraging crowdsourcing platforms to seek novel solutions to data-driven problems. Crowdsourcing innovation problems to the data science community frequently take the form of public contests. Existing literature studied the mechanism and design of open innovation contests. However, the data science contests have a number of...
The use of RPE as a measure of Internal load has become a common methodology used in team sports owing to its low cost. The aim of this study was to build a machine learning process able to describe the players' RPE by the external load extracted from the GPS. In this paper, we propose a multidimensional approach to assess the RPE in professional soccer which is based on GPS measurements and machine...
Information networks such as social networks, publication networks, and the World Wide Web are ubiquitous in the real world. Traditionally, adjacency matrices are used to represent the networks. However, adjacency matrices are too sparse and too high dimensional when the scale of the networks is large. Network embedding, which aims to learn low-dimensional continuous representations for nodes, has...
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