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Pleasant Route Suggestion based on Color and Object Rates

Authors:

Adam JatowtAuthors Info & Claims

WSDM '19: Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining

Pages 786 - 789

https://doi.org/10.1145/3289600.3290611

Published: 30 January 2019 Publication History

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Abstract

For a tourist who wishes to stroll in an unknown city, it is useful to have a recommendation of not just the shortest routes but also routes that are pleasant. This paper demonstrates a system that provides pleasant route recommendation. Currently, we focus on routes that have much green and bright views. The system measures pleasure scores by extracting colors or objects in Google Street View panorama images and re-ranks shortest paths in the order of the computed pleasure scores. The current prototype provides route recommendation for city areas in Tokyo, Kyoto and San Francisco.

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Cited By

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Jiang QTang XWang J(2024)QoS-Aware Route Navigation for Pedestrians Using 5G Cellular Networks2024 IEEE 35th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)10.1109/PIMRC59610.2024.10817225(1-6)Online publication date: 2-Sep-2024
https://doi.org/10.1109/PIMRC59610.2024.10817225
Xiao YSong M(2024)How are urban design qualities associated with perceived walkability? An AI approach using street view images and deep learningInternational Journal of Urban Sciences10.1080/12265934.2024.2429824(1-26)Online publication date: 20-Nov-2024
https://doi.org/10.1080/12265934.2024.2429824
Kim EGong Y(2023)The Smart City and Healthy Walking: An Environmental Comparison Between Healthy and the Shortest Route ChoicesUrban Planning10.17645/up.v8i2.64078:2Online publication date: 9-Mar-2023
https://doi.org/10.17645/up.v8i2.6407
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Index Terms

Pleasant Route Suggestion based on Color and Object Rates
1. Information systems
  1. Information retrieval
    1. Retrieval tasks and goals
      1. Recommender systems
  2. World Wide Web
    1. Web applications

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Published In

WSDM '19: Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining

January 2019

874 pages

ISBN:9781450359405

DOI:10.1145/3289600

General Chairs:
J. Shane Culpepper
RMIT University
,
Alistair Moffat
The University of Melbourne
,
Program Chairs:
Paul N. Bennett
Microsoft
,
Kristina Lerman
University of Southern California

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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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 30 January 2019

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MIC SCOPE
Japan Society for the Promotion of Science

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WSDM '19

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WSDM '19: The Twelfth ACM International Conference on Web Search and Data Mining

February 11 - 15, 2019

Melbourne VIC, Australia

Acceptance Rates

WSDM '19 Paper Acceptance Rate 84 of 511 submissions, 16%;

Overall Acceptance Rate 498 of 2,863 submissions, 17%

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Cited By

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Jiang QTang XWang J(2024)QoS-Aware Route Navigation for Pedestrians Using 5G Cellular Networks2024 IEEE 35th International Symposium on Personal, Indoor and Mobile Radio Communications (PIMRC)10.1109/PIMRC59610.2024.10817225(1-6)Online publication date: 2-Sep-2024
https://doi.org/10.1109/PIMRC59610.2024.10817225
Xiao YSong M(2024)How are urban design qualities associated with perceived walkability? An AI approach using street view images and deep learningInternational Journal of Urban Sciences10.1080/12265934.2024.2429824(1-26)Online publication date: 20-Nov-2024
https://doi.org/10.1080/12265934.2024.2429824
Kim EGong Y(2023)The Smart City and Healthy Walking: An Environmental Comparison Between Healthy and the Shortest Route ChoicesUrban Planning10.17645/up.v8i2.64078:2Online publication date: 9-Mar-2023
https://doi.org/10.17645/up.v8i2.6407
KAWAI YLI DONO S(2023)Practical Technologies for Analysis, Recommendation, and Visualization of User Behavior and Social Environment Dataユーザ行動と社会環境データの分析・推薦・可視化の実践的応用技術IEICE ESS Fundamentals Review10.1587/essfr.17.1_7217:1(72-80)Online publication date: 1-Jul-2023
https://doi.org/10.1587/essfr.17.1_72
Liu SLong YZhang LHuang Y(2023)Urban high‐quality navigation path planning that integrates human emotion perception learningTransactions in GIS10.1111/tgis.1311927:8(2297-2319)Online publication date: 23-Nov-2023
https://doi.org/10.1111/tgis.13119
Yamashita OYokoyama S(2022)Preference aware route recommendation using one billion geotagged tweetsProceedings of the 6th ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising10.1145/3557992.3565990(1-10)Online publication date: 1-Nov-2022
https://dl.acm.org/doi/10.1145/3557992.3565990
Anzai SMurayama TYada SWakayama SAramaki E(2021)Finding "retro" places in JapanProceedings of the 5th ACM SIGSPATIAL International Workshop on Location-based Recommendations, Geosocial Networks and Geoadvertising10.1145/3486183.3490999(1-4)Online publication date: 2-Nov-2021
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Ito KBiljecki F(2021)Assessing bikeability with street view imagery and computer visionTransportation Research Part C: Emerging Technologies10.1016/j.trc.2021.103371132(103371)Online publication date: Nov-2021
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Liu JWood KLim K(2021)Strategic and Crowd-Aware Itinerary RecommendationMachine Learning and Knowledge Discovery in Databases: Applied Data Science Track10.1007/978-3-030-67667-4_5(69-85)Online publication date: 25-Feb-2021
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Siriaraya PWang YZhang YWakamiya SJeszenszky PKawai YJatowt A(2020)Beyond the Shortest Route: A Survey on Quality-Aware Route Navigation for PedestriansIEEE Access10.1109/ACCESS.2020.30119248(135569-135590)Online publication date: 2020
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