@inproceedings{71a7209d09154a82a67a8ba12ca9ca05,
title = "Where to park? predicting free parking spots in unmonitored city areas",
abstract = "Several smart cities around the world have begun monitoring parking areas in order to estimate free spots and help drivers that are looking for parking. The current results are indeed promising, however, this approach is limited by the high costs of sensors that need to be installed throughout the city in order to achieve an accurate estimation rate. This work investigates the extension of estimating parking information from areas equipped with sensors to areas that are missing them. To this end, similarity values between city neighborhoods are computed based on background data, i.e., from geographic information systems. Using the derived similarity values, we analyze the adaptation of occupancy rates from monitored-to unmonitored parking areas.",
keywords = "Data mining, Machine learning, Semantic annotation, Smart parking",
author = "Andrei Ionita and Andr{\'e} Pomp and Michael Cochez and Tobias Meisen and Stefan Decker",
year = "2018",
month = jun,
day = "25",
doi = "10.1145/3227609.3227648",
language = "English",
series = "ACM International Conference Proceeding Series",
publisher = "Association for Computing Machinery",
editor = "Costin Badica and Rajendra Akerkar and Mirjana Ivanovic and Milos Savic and Milos Radovanovic and Sang-Wook Kim and Riccardo Rosati and Yannis Manolopoulos",
booktitle = "WIMS 2018 - 8th International Conference on Web Intelligence, Mining and Semantics",
note = "8th International Conference on Web Intelligence, Mining and Semantics, WIMS 2018 ; Conference date: 25-06-2018 Through 27-06-2018",
}