The Science and Information (SAI) Organization
  • Home
  • About Us
  • Journals
  • Conferences
  • Contact Us

Publication Links

  • IJACSA
  • Author Guidelines
  • Publication Policies
  • Metadata Harvesting (OAI2)
  • Digital Archiving Policy

IJACSA

  • About the Journal
  • Call for Papers
  • Author Guidelines
  • Fees/ APC
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Apply as a Reviewer

IJARAI

  • About the Journal
  • Archives
  • Indexing & Archiving
  • Editorial Board

Special Issues

  • Home
  • Archives
  • Proposals
  • Guest Editors

Computing Conference 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Intelligent Systems Conference (IntelliSys) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future Technologies Conference (FTC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact

Future of Information and Communication Conference (FICC) 2021

  • Home
  • Call for Papers
  • Submit your Paper/Poster
  • Register
  • Venue
  • Contact
  • Home
  • Call for Papers
  • Guidelines
  • Fees
  • Submit your Paper
  • Current Issue
  • Archives
  • Indexing
  • Editors
  • Reviewers
  • Subscribe

Article Details

Copyright Statement: This is an open access article licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, even commercially as long as the original work is properly cited.

A Japanese Tourism Recommender System with Automatic Generation of Seasonal Feature Vectors

Author 1: Guan-Shen Fang
Author 2: Sayaka Kamei
Author 3: Satoshi Fujita

Download PDF

Digital Object Identifier (DOI) : 10.14569/IJACSA.2017.080645

Article Published in International Journal of Advanced Computer Science and Applications(IJACSA), Volume 8 Issue 6, 2017.

  • Abstract and Keywords
  • How to Cite this Article
  • {} BibTeX Source

Abstract: Tourism recommender systems have been widely used in our daily life to recommend tourist spots to users meeting their preference. In this paper, we propose a contentbased tourism recommender system considering travel season of users. In order to characterize seasonal variable features of spots,the proposed system generates seasonal feature vectors in three steps: 1) to identify the vocabulary concerned through Wikipedia; 2) to identify the trend over all spots through Twitter for each season; and 3) to highlight the weight of words contained in each identified trend. In the decision of recommendation, it does not only match the user profile with features of spots but also takes user’s travel season into account. The effectiveness of the proposed system is evaluated by a series of experiments, i.e.computer simulation and questionnaire evaluation. The result indicates that: 1) those vectors certainly reflect the similarity of spots for designated time period, and 2) with using such vectors of spots, the system successfully realized a tourism seasonal recommendation.

Keywords: Tourism recommender system; seasonal feature vector; Wikipedia; Twitter

Guan-Shen Fang, Sayaka Kamei and Satoshi Fujita, “A Japanese Tourism Recommender System with Automatic Generation of Seasonal Feature Vectors” International Journal of Advanced Computer Science and Applications(IJACSA), 8(6), 2017. http://dx.doi.org/10.14569/IJACSA.2017.080645

@article{Fang2017,
title = {A Japanese Tourism Recommender System with Automatic Generation of Seasonal Feature Vectors},
journal = {International Journal of Advanced Computer Science and Applications},
doi = {10.14569/IJACSA.2017.080645},
url = {http://dx.doi.org/10.14569/IJACSA.2017.080645},
year = {2017},
publisher = {The Science and Information Organization},
volume = {8},
number = {6},
author = {Guan-Shen Fang and Sayaka Kamei and Satoshi Fujita}
}


IJACSA

Upcoming Conferences

Future of Information and Communication Conference (FICC) 2021

29-30 April 2021

  • Virtual

Computing Conference 2021

15-16 July 2021

  • London, United Kingdom

IntelliSys 2021

2-3 September 2021

  • Amsterdam, The Netherlands

Future Technologies Conference (FTC) 2021

28-29 October 2021

  • Vancouver, Canada
The Science and Information (SAI) Organization
BACK TO TOP

Computer Science Journal

  • About the Journal
  • Call for Papers
  • Submit Paper
  • Indexing

Our Conferences

  • Computing Conference
  • Intelligent Systems Conference
  • Future Technologies Conference
  • Communication Conference

Help & Support

  • Contact Us
  • About Us
  • Terms and Conditions
  • Privacy Policy

© 2018 The Science and Information (SAI) Organization Limited. Registered in England and Wales. Company Number 8933205. All rights reserved. thesai.org