research-article

Generating Distributed Representation of User Movement for Extracting Detour Spots

Authors:

Masaharu Hirota,

Hiroshi IshikawaAuthors Info & Claims

MEDES '19: Proceedings of the 11th International Conference on Management of Digital EcoSystems

Pages 250 - 255

https://doi.org/10.1145/3297662.3365826

Published: 10 January 2020 Publication History

Abstract

Owing to the increasing popularity of mobile devices embedded with a Global Positioning System (GPS) sensor, large amounts of user-generated content containing spatial information have been uploaded to social media websites, such as Flickr or Twitter. That content posted from tourist spots can be used to search for and recommend other tourism spots and routes. Recent research papers in the field of Natural Language Processing (NLP) have proposed learning a distributed representation of words using embedding algorithms. In this paper, we use a Skip-gram model to analyze user movements obtained from social media websites. We propose a new Skip-gramgemodel to learn movements between a pair of locations quantified by the latitude and the longitude. The embedding vectors by our model represents user movements between the locations. We successfully demonstrated that the embedded vectors generated with our proposed method can extract detour spots for tourism spots and routes.

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Cited By

Wei ZDan TDing JLaurienti PWu G(2024)Representing Functional Connectivity with Structural Detour: A New Perspective to Decipher Structure-Function Coupling MechanismMedical Image Computing and Computer Assisted Intervention – MICCAI 202410.1007/978-3-031-72069-7_35(367-377)Online publication date: 4-Oct-2024
https://doi.org/10.1007/978-3-031-72069-7_35
Fushimi TOtaki H(2023)A Method for Presenting Multiple Routes Considering Distance and Landscape Probability for Automotive Navigation Systems2023 IEEE International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)10.1109/WI-IAT59888.2023.00039(249-255)Online publication date: 26-Oct-2023
https://doi.org/10.1109/WI-IAT59888.2023.00039
Hirota MOda T(2021)An Approach of Trajectory Clustering Using Distributed Representation of User Movement2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech)10.1109/LifeTech52111.2021.9391965(75-76)Online publication date: 9-Mar-2021
https://doi.org/10.1109/LifeTech52111.2021.9391965

Index Terms

Generating Distributed Representation of User Movement for Extracting Detour Spots
1. Information systems
  1. Information systems applications
    1. Spatial-temporal systems
      1. Geographic information systems
      2. Location based services

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Published In

cover image ACM Other conferences

MEDES '19: Proceedings of the 11th International Conference on Management of Digital EcoSystems

November 2019

350 pages

ISBN:9781450362382

DOI:10.1145/3297662

General Chairs:
Richard Chbeir
University of Pau and Pays de l'Adour, France
,
Yannis Manolopoulos
Open University of Cyprus, Cyprus
,
Program Chairs:
Sergio Ilarri
University of Zaragoza, Spain
,
Apostolos Papadopoulos
Aristotle University of Thessaloniki, Greece

Copyright © 2019 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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SIGAPP: ACM Special Interest Group on Applied Computing

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 10 January 2020

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MEDES '19

MEDES '19: 11th International Conference on Management of Digital EcoSystems

November 12 - 14, 2019

Limassol, Cyprus

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MEDES '19 Paper Acceptance Rate 41 of 102 submissions, 40%;

Overall Acceptance Rate 267 of 682 submissions, 39%

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Cited By

Wei ZDan TDing JLaurienti PWu G(2024)Representing Functional Connectivity with Structural Detour: A New Perspective to Decipher Structure-Function Coupling MechanismMedical Image Computing and Computer Assisted Intervention – MICCAI 202410.1007/978-3-031-72069-7_35(367-377)Online publication date: 4-Oct-2024
https://doi.org/10.1007/978-3-031-72069-7_35
Fushimi TOtaki H(2023)A Method for Presenting Multiple Routes Considering Distance and Landscape Probability for Automotive Navigation Systems2023 IEEE International Conference on Web Intelligence and Intelligent Agent Technology (WI-IAT)10.1109/WI-IAT59888.2023.00039(249-255)Online publication date: 26-Oct-2023
https://doi.org/10.1109/WI-IAT59888.2023.00039
Hirota MOda T(2021)An Approach of Trajectory Clustering Using Distributed Representation of User Movement2021 IEEE 3rd Global Conference on Life Sciences and Technologies (LifeTech)10.1109/LifeTech52111.2021.9391965(75-76)Online publication date: 9-Mar-2021
https://doi.org/10.1109/LifeTech52111.2021.9391965
Tanaka HSaga TNakamura S(2021)Clustering of Human Movement Trajectories based on Distributional Representations Derived from Bi-directional LSTM Network with Geographical Coordinates2021 IEEE International Conference on Big Data (Big Data)10.1109/BigData52589.2021.9671400(2936-2940)Online publication date: 15-Dec-2021
https://doi.org/10.1109/BigData52589.2021.9671400

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