A route recommendation method based on personal preferences by monte-carlo tree search

Yuta Ishizaki, Toshinori Takayama, Nozomu Togawa

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

1 Citation (Scopus)

Abstract

In this paper, we propose a route recommendation method, called P-UCT method, considering individual user's preferences utilizing Monte-Carlo tree search. In the proposed method, we firstly extract route features based on the route recommendation history of every user and construct a route evaluator based on Support Vector Machine (SVM). After that, the method generates a random route from a start point to an end point by Monte-Carlo tree search. The route evaluator determines how well every generated route matches the user's preferences. By repeating the evaluation, the method obtains the route, which must be closest to the user's preferences. Experimental results demonstrate that the proposed method outperforms the existing method from the viewpoint of the average evaluation scores.

Original languageEnglish
Title of host publicationProceedings - 2019 IEEE 9th International Conference on Consumer Electronics, ICCE-Berlin 2019
EditorsGordan Velikic, Christian Gross
PublisherIEEE Computer Society
Pages404-409
Number of pages6
ISBN (Electronic)9781728127453
DOIs
Publication statusPublished - 2019 Sep
Event9th IEEE International Conference on Consumer Electronics, ICCE-Berlin 2019 - Berlin, Germany
Duration: 2019 Sep 82019 Sep 11

Publication series

NameIEEE International Conference on Consumer Electronics - Berlin, ICCE-Berlin
Volume2019-September
ISSN (Print)2166-6814
ISSN (Electronic)2166-6822

Conference

Conference9th IEEE International Conference on Consumer Electronics, ICCE-Berlin 2019
Country/TerritoryGermany
CityBerlin
Period19/9/819/9/11

Keywords

  • Monte-Carlo tree search
  • Route recommendation
  • SVM
  • UCT

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Industrial and Manufacturing Engineering
  • Media Technology

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