Non-Negative Matrix Factorization of Story Watching Time of Tourists for Best Sightseeing Spot and Preference


Motoki Seguchi1, Fumiko Harada2 and Hiromitsu Shimakawa1, 1Ritsumeikan University, Japan, 2Connect Dot Ltd., Japan


In this research, we propose a method of recommending the best sightseeing spot through watching stories of sightseeing spots. It predicts the rating for each sightseeing spot of a target tourist based on Non-negative Matrix Factorization on the story watching times and ratings of tourists. We also propose to estimate the degree of the target tourist’s preference for a sightseeing spot. Tourists visit a sightseeing spot for a certain purpose of tourism. The preferences of tourists appear prominently in their purposes of tourism. In addition, the degree of the tourists’ preferences for sightseeing spots differs depending on the sightseeing spot. If we can estimate the degree of preference of a tourist, it will be possible to recommend a sightseeing spot that can achieve his purpose of tourism.


Sightseeing, Recommendation, Interest Estimation, Story Watching, Preference.

Full Text  Volume 10, Number 11