poster

Mining mobility user profiles for car pooling

Authors:

Roberto Trasarti,

Fosca GiannottiAuthors Info & Claims

KDD '11: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 1190 - 1198

https://doi.org/10.1145/2020408.2020591

Published: 21 August 2011 Publication History

Abstract

In this paper we introduce a methodology for extracting mobility profiles of individuals from raw digital traces (in particular, GPS traces), and study criteria to match individuals based on profiles. We instantiate the profile matching problem to a specific application context, namely proactive car pooling services, and therefore develop a matching criterion that satisfies various basic constraints obtained from the background knowledge of the application domain. In order to evaluate the impact and robustness of the methods introduced, two experiments are reported, which were performed on a massive dataset containing GPS traces of private cars: (i) the impact of the car pooling application based on profile matching is measured, in terms of percentage shareable traffic; (ii) the approach is adapted to coarser-grained mobility data sources that are nowadays commonly available from telecom operators. In addition the ensuing loss in precision and coverage of profile matches is measured.

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Cited By

Wen DLi YLau F(2024)A Survey of Machine Learning-Based Ride-Hailing PlanningIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.334517425:6(4734-4753)Online publication date: Jun-2024
https://doi.org/10.1109/TITS.2023.3345174
Nanni MAlamdari OBonavita ACintia P(2024)From Fossil Fuel to Electricity: Studying the Impact of EVs on the Daily Mobility Life of UsersIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.334074225:6(5780-5790)Online publication date: Jun-2024
https://doi.org/10.1109/TITS.2023.3340742
Bhatnagar PL GB GC SJ S(2024)Mobile Application for Carpooling with Journey mate Feature2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)10.1109/COMSNETS59351.2024.10427139(1088-1093)Online publication date: 3-Jan-2024
https://doi.org/10.1109/COMSNETS59351.2024.10427139
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Index Terms

Mining mobility user profiles for car pooling
1. Information systems

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Published In

cover image ACM Conferences

KDD '11: Proceedings of the 17th ACM SIGKDD international conference on Knowledge discovery and data mining

August 2011

1446 pages

ISBN:9781450308137

DOI:10.1145/2020408

General Chair:
Chid Apte
IBM Research
,
Program Chairs:
Joydeep Ghosh
UT Austin
,
Padhraic Smyth
UC Irvine

Copyright © 2011 ACM.

Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 21 August 2011

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KDD '11

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KDD '11: The 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

August 21 - 24, 2011

California, San Diego, USA

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Overall Acceptance Rate 1,133 of 8,635 submissions, 13%

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Cited By

Wen DLi YLau F(2024)A Survey of Machine Learning-Based Ride-Hailing PlanningIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.334517425:6(4734-4753)Online publication date: Jun-2024
https://doi.org/10.1109/TITS.2023.3345174
Nanni MAlamdari OBonavita ACintia P(2024)From Fossil Fuel to Electricity: Studying the Impact of EVs on the Daily Mobility Life of UsersIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2023.334074225:6(5780-5790)Online publication date: Jun-2024
https://doi.org/10.1109/TITS.2023.3340742
Bhatnagar PL GB GC SJ S(2024)Mobile Application for Carpooling with Journey mate Feature2024 16th International Conference on COMmunication Systems & NETworkS (COMSNETS)10.1109/COMSNETS59351.2024.10427139(1088-1093)Online publication date: 3-Jan-2024
https://doi.org/10.1109/COMSNETS59351.2024.10427139
Koutsaki EVardakis GPapadakis N(2023)Spatiotemporal Data Mining Problems and MethodsAnalytics10.3390/analytics20200272:2(485-508)Online publication date: 14-Jun-2023
https://doi.org/10.3390/analytics2020027
Tolomei GPinelli FSilvestri F(2022)Editorial: Human-Interpretable Machine LearningFrontiers in Big Data10.3389/fdata.2022.9566255Online publication date: 20-Jun-2022
https://doi.org/10.3389/fdata.2022.956625
Zhou JLi DLiu M(2022)BETA: From Behavior Sequentializing to Task Mapping in Mobile CrowdsensingIEEE Internet of Things Journal10.1109/JIOT.2022.31646729:19(18960-18972)Online publication date: 1-Oct-2022
https://doi.org/10.1109/JIOT.2022.3164672
Nanni MGuidotti RBonavita AAlamdari O(2022)City indicators for geographical transfer learning: an application to crash predictionGeoInformatica10.1007/s10707-022-00464-326:4(581-612)Online publication date: 22-Mar-2022
https://doi.org/10.1007/s10707-022-00464-3
Martinelli FMarulli FMercaldo FSantone A(2021)Neural Networks for Driver Behavior AnalysisElectronics10.3390/electronics1003034210:3(342)Online publication date: 1-Feb-2021
https://doi.org/10.3390/electronics10030342
Celes CBoukerche ALoureiro A(2021)Mobility Trace Analysis for Intelligent Vehicular NetworksACM Computing Surveys10.1145/344667954:3(1-38)Online publication date: 17-Apr-2021
https://dl.acm.org/doi/10.1145/3446679
Martelli FRenda M(2021)Comparison of Trip Matching Algorithms for Mobility Sharing Applications2021 IEEE 22nd International Symposium on a World of Wireless, Mobile and Multimedia Networks (WoWMoM)10.1109/WoWMoM51794.2021.00051(274-279)Online publication date: Jun-2021
https://doi.org/10.1109/WoWMoM51794.2021.00051
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