Affective Recommendation System for Tourists by Using Emotion Generating Calculations

TL;DR

This paper presents an emotion-based tourist recommendation system that evaluates user feelings through emotion generating calculations to suggest sightseeing spots and local food, demonstrated via Hiroshima sightseeing experiments.

Contribution

Developed an Android-based emotion-aware recommendation system integrating EGC and MSTN to personalize tourist suggestions based on user feelings.

Findings

Effective estimation of user emotions at sightseeing spots

Personalized recommendations based on emotion calculations

Successful experimental validation during Hiroshima sightseeing

Abstract

An emotion orientated intelligent interface consists of Emotion Generating Calculations (EGC) and Mental State Transition Network (MSTN). We have developed the Android EGC application software which the agent works to evaluate the feelings in the conversation. In this paper, we develop the tourist information system which can estimate the user's feelings at the sightseeing spot. The system can recommend the sightseeing spot and the local food corresponded to the user's feeling. The system calculates the recommendation list by the estimate function which consists of Google search results, the important degree of a term at the sightseeing website, and the the aroused emotion by EGC. In order to show the effectiveness, this paper describes the experimental results for some situations during Hiroshima sightseeing.