A group travel recommender system based on collaborative filtering and group approximate constraint satisfaction

Jin Lu He, Il Young Choi, Jae Kyeong Kim

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

1 Citation (Scopus)

Abstract

In this research, a modified CF (Collaborative filtering) procedure is suggested to decide a destination for group travel planning service. Furthermore, a composite travel product includes hotel, and attraction in addition to the selection of a destination. For such a purpose, individual user’s personal requirements are represented by constraints, and a group constraints are constructed based on group member’s constraints. A two-phase group approximate satisfying constraint procedure is suggested to automate group decision making procedure for selecting their trip packages to improve group tourists’ convenience and their satisfaction. A group travel recommendation is suggested with an illustrative example and an experimental design is suggested to validate the suggested procedure.

Original languageEnglish
Title of host publicationIntelligent Human Systems Integration - Proceedings of the 3rd International Conference on Intelligent Human Systems Integration IHSI 2020
Subtitle of host publicationIntegrating People and Intelligent Systems
EditorsTareq Ahram, Waldemar Karwowski, Alberto Vergnano, Francesco Leali, Redha Taiar
PublisherSpringer
Pages1178-1183
Number of pages6
ISBN (Print)9783030395117
DOIs
Publication statusPublished - 2020
Event3rd International Conference on Intelligent Human Systems Integration, IHSI 2020 - Modena, Italy
Duration: 19 Feb 202021 Feb 2020

Publication series

NameAdvances in Intelligent Systems and Computing
Volume1131 AISC
ISSN (Print)2194-5357
ISSN (Electronic)2194-5365

Conference

Conference3rd International Conference on Intelligent Human Systems Integration, IHSI 2020
Country/TerritoryItaly
CityModena
Period19/02/2021/02/20

Bibliographical note

Publisher Copyright:
© Springer Nature Switzerland AG 2020.

Keywords

  • Approximate constraint satisfaction
  • Collaborative filtering
  • Group recommender systems
  • Travel recommender system

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