_:naedc22425727445e9330c0ccdd05e7d9xb30
<http://schema.org/description>
"This papers presents a deep learning-based framework to predict crowdsourced\nservice availability spatially and temporally. A novel two-stage prediction\nmodel is introduced based on historical spatio-temporal traces of mobile\ncrowdsourced services. The prediction model first clusters mobile crowdsourced\nservices into regions. The availability prediction of a mobile crowdsourced\nservice at a certain location and time is then formulated as a classification\nproblem. To determine the availability duration of predicted mobile\ncrowdsourced services, we formulate a forecasting task of time series using the\nGramian Angular Field. We validated the effectiveness of the proposed framework\nthrough multiple experiments."
<https://deepai.org/profile/athman-bouguettaya>