Analysis of diverse tourist information distributed across the internet

Takeshi Tsuchiya, Hiroo Hirose, Tadashi Miyosawa, Tetsuyasu Yamada, Hiroaki Sawano, Keiichi Koyanagi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Herein, we propose and discuss a new method for analyzing various types of tourist information about the Suwa area of Nagano Prefecture, Japan, available on the Internet. This information includes not only long sentences that can be found on web pages and in blogs, but also short sentences comprising a few words posted on social media. In this paper, we propose a novel method based on a neural network, called paragraph vector, for expressing relationships between words included in sentences. Our method achieves high retrieval accuracy even across social media posts comprising just a few words. Based on our evaluation results, the proposed method outperforms the conventional information retrieval technique wherein sufficient accuracy cannot be achieved as it is based on the occurrence probability of words in sentences. This improvement is achieved by using the word order as an input feature to the neural network model.

Original languageEnglish
Title of host publicationFuture Data and Security Engineering- 5th International Conference, FDSE 2018, Proceedings
EditorsTran Khanh Dang, Nam Thoai, Josef Küng, Roland Wagner, Makoto Takizawa
PublisherSpringer
Pages413-422
Number of pages10
ISBN (Print)9783030031916
DOIs
Publication statusPublished - 2018
Event5th International Conference on Future Data and Security Engineering, FDSE 2018 - Ho Chi Minh City, Viet Nam
Duration: 2018 Nov 282018 Nov 30

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume11251 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference5th International Conference on Future Data and Security Engineering, FDSE 2018
CountryViet Nam
CityHo Chi Minh City
Period18/11/2818/11/30

Keywords

  • Paragraph vector
  • SNS
  • Tourist information

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Tsuchiya, T., Hirose, H., Miyosawa, T., Yamada, T., Sawano, H., & Koyanagi, K. (2018). Analysis of diverse tourist information distributed across the internet. In T. K. Dang, N. Thoai, J. Küng, R. Wagner, & M. Takizawa (Eds.), Future Data and Security Engineering- 5th International Conference, FDSE 2018, Proceedings (pp. 413-422). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11251 LNCS). Springer. https://doi.org/10.1007/978-3-030-03192-3_31