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An energy-efficient mobile recommender system

Authors:

Alexander Tuzhilin,

Marco Gruteser,

Michael PazzaniAuthors Info & Claims

KDD '10: Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining

Pages 899 - 908

https://doi.org/10.1145/1835804.1835918

Published: 25 July 2010 Publication History

Abstract

The increasing availability of large-scale location traces creates unprecedent opportunities to change the paradigm for knowledge discovery in transportation systems. A particularly promising area is to extract energy-efficient transportation patterns (green knowledge), which can be used as guidance for reducing inefficiencies in energy consumption of transportation sectors. However, extracting green knowledge from location traces is not a trivial task. Conventional data analysis tools are usually not customized for handling the massive quantity, complex, dynamic, and distributed nature of location traces. To that end, in this paper, we provide a focused study of extracting energy-efficient transportation patterns from location traces. Specifically, we have the initial focus on a sequence of mobile recommendations. As a case study, we develop a mobile recommender system which has the ability in recommending a sequence of pick-up points for taxi drivers or a sequence of potential parking positions. The goal of this mobile recommendation system is to maximize the probability of business success. Along this line, we provide a Potential Travel Distance (PTD) function for evaluating each candidate sequence. This PTD function possesses a monotone property which can be used to effectively prune the search space. Based on this PTD function, we develop two algorithms, LCP and SkyRoute, for finding the recommended routes. Finally, experimental results show that the proposed system can provide effective mobile sequential recommendation and the knowledge extracted from location traces can be used for coaching drivers and leading to the efficient use of energy.

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Cited By

Wang DLi WPan J(2024)Large-Scale Mixed Traffic Control Using Dynamic Vehicle Routing and Privacy-Preserving CrowdsourcingIEEE Internet of Things Journal10.1109/JIOT.2023.333529211:2(1981-1989)Online publication date: 15-Jan-2024
https://doi.org/10.1109/JIOT.2023.3335292
Zhang SLuo ZYang LTeng FLi T(2024)A survey of route recommendations: Methods, applications, and opportunitiesInformation Fusion10.1016/j.inffus.2024.102413(102413)Online publication date: Apr-2024
https://doi.org/10.1016/j.inffus.2024.102413
Ray SDey SPaul P(2024)Mobile Choice SystemIntelligent Electrical Systems and Industrial Automation10.1007/978-981-97-6806-6_20(243-251)Online publication date: 29-Nov-2024
https://doi.org/10.1007/978-981-97-6806-6_20
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Index Terms

An energy-efficient mobile recommender system
1. Information systems
  1. Information systems applications
    1. Data mining

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Published In

cover image ACM Conferences

KDD '10: Proceedings of the 16th ACM SIGKDD international conference on Knowledge discovery and data mining

July 2010

1240 pages

ISBN:9781450300551

DOI:10.1145/1835804

General Chairs:
Bharat Rao
Siemens
,
Balaji Krishnapuram
Siemens
,
Program Chairs:
Andrew Tomkins
Google Inc.
,
Qiang Yang
Hong Kong University of Science and Technology

Copyright © 2010 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: 25 July 2010

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KDD '10

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KDD '10: The 16th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining

July 25 - 28, 2010

DC, Washington, USA

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

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Cited By

Wang DLi WPan J(2024)Large-Scale Mixed Traffic Control Using Dynamic Vehicle Routing and Privacy-Preserving CrowdsourcingIEEE Internet of Things Journal10.1109/JIOT.2023.333529211:2(1981-1989)Online publication date: 15-Jan-2024
https://doi.org/10.1109/JIOT.2023.3335292
Zhang SLuo ZYang LTeng FLi T(2024)A survey of route recommendations: Methods, applications, and opportunitiesInformation Fusion10.1016/j.inffus.2024.102413(102413)Online publication date: Apr-2024
https://doi.org/10.1016/j.inffus.2024.102413
Ray SDey SPaul P(2024)Mobile Choice SystemIntelligent Electrical Systems and Industrial Automation10.1007/978-981-97-6806-6_20(243-251)Online publication date: 29-Nov-2024
https://doi.org/10.1007/978-981-97-6806-6_20
Lin XHuang ZYe YDong JFeng HZheng P(2023)Effects of Aging on Taxi Service Performance: A Comparative Study Based on Different Age GroupsSustainability10.3390/su15221609615:22(16096)Online publication date: 20-Nov-2023
https://doi.org/10.3390/su152216096
Wang aLin XHe FXu ZShen Z(2023)On the Relocation Game of Ride-Hailing Platforms with Non-Atomic DriversSSRN Electronic Journal10.2139/ssrn.4454177Online publication date: 2023
https://doi.org/10.2139/ssrn.4454177
Makhdomi AGillani I(2023)Towards a Greener and Fairer Transportation System: A Survey of Route Recommendation TechniquesACM Transactions on Intelligent Systems and Technology10.1145/362782515:1(1-57)Online publication date: 19-Dec-2023
https://dl.acm.org/doi/10.1145/3627825
Hu MZhang XLi YZhou XLuo JSingh ASun YAkoglu LGunopulos DYan XKumar ROzcan FYe J(2023)ST-iFGSM: Enhancing Robustness of Human Mobility Signature Identification Model via Spatial-Temporal Iterative FGSMProceedings of the 29th ACM SIGKDD Conference on Knowledge Discovery and Data Mining10.1145/3580305.3599513(764-774)Online publication date: 6-Aug-2023
https://dl.acm.org/doi/10.1145/3580305.3599513
Lu YWang YChen YXiong Y(2023)The role of data‐based intelligence and experience on time efficiency of taxi drivers: An empirical investigation using large‐scale sensor dataProduction and Operations Management10.1111/poms.1405632:11(3665-3682)Online publication date: 1-Nov-2023
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Wang TShen ZCao YXu XGong H(2023)Taxi-Cruising Recommendation via Real-Time Information and Historical Trajectory DataIEEE Transactions on Intelligent Transportation Systems10.1109/TITS.2021.309320724:8(7898-7910)Online publication date: Aug-2023
https://doi.org/10.1109/TITS.2021.3093207
Zhang YShen GHan XWang WKong X(2023)Spatio-Temporal Digraph Convolutional Network-Based Taxi Pickup Location RecommendationIEEE Transactions on Industrial Informatics10.1109/TII.2022.318104519:1(394-403)Online publication date: Jan-2023
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