An Innovative Tour Recommendation System

An Innovative Tour Recommendation System for Tourists in Japan

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Abstract1— The paper demonstrates prototype of system that
is capable of suggesting optimal touring plans which are
composed of various points of interest (POI) and take travelers’
preferences and context into account. It systematically collects
and analyzes information on thousands of tourists attraction
areas and geographical nodes of Japan Railway (JR) train
stations together with concurrent weather information,
estimated travel time, associated expenses, and lists of multiple
cultural events in order to demonstrate practicality as well as
reliability of the system. A programmatic approach based on the
heuristic greedy search is employed for transforming the
obtained data into informative routes. It demonstrates the
feasibility of the approach through its mobile prototype on web
platform and tests it under various scenarios in eight different
places in Japan which includes Tokyo, Osaka, Kyoto, Kobe,
Yokohama, Nagoya, Fukuoka and Sapporo. Its result and the
performance can be considered as a stepping stone towards a
more localized and practical recommendation system in the field
of tourism in the near future.
Keywords— e-tourism, travel planning system, web scraping,
modeling, and data mining.