research-article

Preference Aware Travel Route Recommendation with Temporal Influence

Authors:

Madhuri Debnath,

Praveen Kumar Tripathi,

Ashis Kumer Biswas,

Ramez ElmasriAuthors Info & Claims

LocalRec'18: Proceedings of the 2nd ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks

Article No.: 2, Pages 1 - 9

https://doi.org/10.1145/3282825.3282829

Published: 06 November 2018 Publication History

Abstract

There have been vast advances and rapid growth in Location based social networking (LBSN) services in recent years. Travel route recommendation is one of the most important applications in the LBSN services. Travel route recommendation provides users a sequence of POIs (Point of Interests) as a route to visit. In this paper, we propose to recommend time-aware and preference-aware travel routes consisting of a sequence of POI locations with corresponding time information. It helps users not only to explore interesting locations in a new city, but also it will help to plan the entire trip with those locations with the approximated time information under specific time constraints. First, we find the interesting POI locations that considers the following factors: User's categorical preferences, temporal activities and popularity of location. Then, we propose an efficient solution to generate travel routes with those locations including time to visit each location. These travel routes will inform users where to visit and when to visit. We evaluate the efficiency and effectiveness of our solution on a real life LBSN dataset.

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Cited By

Halder SLim KChan JZhang X(2024)A survey on personalized itinerary recommendation: From optimisation to deep learningApplied Soft Computing10.1016/j.asoc.2023.111200152(111200)Online publication date: Feb-2024
https://doi.org/10.1016/j.asoc.2023.111200
Roy SMajumder ASarkar J(2023)An Introduction to Various Parameters of the Point of InterestArtificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications10.2174/9789815136746123010012(189-204)Online publication date: 14-Aug-2023
https://doi.org/10.2174/9789815136746123010012
Han BZheng XGuan MSun LZhang Y(2023)Personalized Route Recommendation with Hybrid Tabu Search Algorithm Based on CrowdsensingInternational Journal of Intelligent Systems10.1155/2023/30548882023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/3054888
Show More Cited By

Index Terms

Preference Aware Travel Route Recommendation with Temporal Influence
1. Information systems
  1. Information systems applications
    1. Collaborative and social computing systems and tools

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Published In

cover image ACM Conferences

LocalRec'18: Proceedings of the 2nd ACM SIGSPATIAL Workshop on Recommendations for Location-based Services and Social Networks

November 2018

46 pages

ISBN:9781450360401

DOI:10.1145/3282825

Editors:
Panagiotis Bouros
Johannes Gutenberg University Mainz, Germany
,
Matthias Renz
Christian-Albrechts-Universität zu Kiel, Germany
,
Dimitris Sacharidis
Technische Universität Wien, Austria

Copyright © 2018 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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SIGSPATIAL: ACM Special Interest Group on Spatial Information

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Association for Computing Machinery

New York, NY, United States

Publication History

Published: 06 November 2018

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SIGSPATIAL '18

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SIGSPATIAL

SIGSPATIAL '18: 26th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems

November 6, 2018

WA, Seattle, USA

Acceptance Rates

LocalRec'18 Paper Acceptance Rate 3 of 4 submissions, 75%;

Overall Acceptance Rate 17 of 26 submissions, 65%

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Cited By

Halder SLim KChan JZhang X(2024)A survey on personalized itinerary recommendation: From optimisation to deep learningApplied Soft Computing10.1016/j.asoc.2023.111200152(111200)Online publication date: Feb-2024
https://doi.org/10.1016/j.asoc.2023.111200
Roy SMajumder ASarkar J(2023)An Introduction to Various Parameters of the Point of InterestArtificial Intelligence and Data Science in Recommendation System: Current Trends, Technologies and Applications10.2174/9789815136746123010012(189-204)Online publication date: 14-Aug-2023
https://doi.org/10.2174/9789815136746123010012
Han BZheng XGuan MSun LZhang Y(2023)Personalized Route Recommendation with Hybrid Tabu Search Algorithm Based on CrowdsensingInternational Journal of Intelligent Systems10.1155/2023/30548882023Online publication date: 1-Jan-2023
https://dl.acm.org/doi/10.1155/2023/3054888
Chen JJiang WWu JLi KLi K(2023)Dynamic Personalized POI Sequence Recommendation with Fine-Grained ContextsACM Transactions on Internet Technology10.1145/358368723:2(1-28)Online publication date: 19-May-2023
https://dl.acm.org/doi/10.1145/3583687
Arefieva VEgger RSchrefl MSchedl MChua TLauw HSi LTerzi ETsaparas P(2023)Travel Bird: A Personalized Destination Recommender with TourBERT and Airbnb ExperiencesProceedings of the Sixteenth ACM International Conference on Web Search and Data Mining10.1145/3539597.3573043(1164-1167)Online publication date: 27-Feb-2023
https://dl.acm.org/doi/10.1145/3539597.3573043
Alix GYanin NPechlivanoglou TLi JHeidari FPapagelis M(2022)A Mobility-based Recommendation System for Mitigating the Risk of Infection during Epidemics2022 23rd IEEE International Conference on Mobile Data Management (MDM)10.1109/MDM55031.2022.00063(292-295)Online publication date: Jun-2022
https://doi.org/10.1109/MDM55031.2022.00063
Vahidnia M(2022)Point-of-interest recommendation in location-based social networks based on collaborative filtering and spatial kernel weightingGeocarto International10.1080/10106049.2022.208662637:26(13949-13972)Online publication date: 15-Jun-2022
https://doi.org/10.1080/10106049.2022.2086626
Halder SLim KChan JZhang X(2022)POI recommendation with queuing time and user interest awarenessData Mining and Knowledge Discovery10.1007/s10618-022-00865-w36:6(2379-2409)Online publication date: 3-Oct-2022
https://doi.org/10.1007/s10618-022-00865-w
Halder SLim KChan JZhang X(2022)Efficient itinerary recommendation via personalized POI selection and pruningKnowledge and Information Systems10.1007/s10115-021-01648-364:4(963-993)Online publication date: 2-Mar-2022
https://doi.org/10.1007/s10115-021-01648-3
Werneck HSilva NViana MPereira AMourão FRocha L(2021)Points of Interest recommendations: Methods, evaluation, and future directionsInformation Systems10.1016/j.is.2021.101789101(101789)Online publication date: Nov-2021
https://doi.org/10.1016/j.is.2021.101789
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