Presentation 2017-11-24
Developing Music Recommendation System Considering Mood Information Based on Discourse with Interactive Agents
Takumi Kakuda, Tadachika Ozono, Toramatsu Shintani,
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Abstract(in Japanese) (See Japanese page)
Abstract(in English) Due to the spread of music distribution service, demand for music recommendation for enormous number of songs is increasing. One of problems of existing recommendation methods such as collaborative filtering is that popular songs are recommended, but recommendations that to be considerate of the user's situation have not been realized. In this research, we propose a method for realizing music recommendation using dialogue agents by estimating mood. The recommendation agents have individual domain knowledge for music. The agents recommend music by estimating mood of a situation of a user. The system uses multiple agents to realize effective recommendation to deal with a variety of preferences of users. We show how the system can be effectively used to recommend music.
Keyword(in Japanese) (See Japanese page)
Keyword(in English) mood estimation / dialogue agent / discourse
Paper # AI2017-14
Date of Issue 2017-11-17 (AI)

Conference Information
Committee AI
Conference Date 2017/11/24(1days)
Place (in Japanese) (See Japanese page)
Place (in English)
Topics (in Japanese) (See Japanese page)
Topics (in English)
Chair Tsunenori Mine(Kyushu Univ.)
Vice Chair Daisuke Katagami(Tokyo Polytechnic Univ.) / Naoki Fukuta(Shizuoka Univ.)
Secretary Daisuke Katagami(Ritsumeikan Univ.) / Naoki Fukuta(Univ. of Electro-Comm.)
Assistant Yuko Sakurai(AIST)

Paper Information
Registration To Technical Committee on Artificial Intelligence and Knowledge-Based Processing
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Developing Music Recommendation System Considering Mood Information Based on Discourse with Interactive Agents
Sub Title (in English)
Keyword(1) mood estimation
Keyword(2) dialogue agent
Keyword(3) discourse
1st Author's Name Takumi Kakuda
1st Author's Affiliation Nagoya Institute of Technology(NIT)
2nd Author's Name Tadachika Ozono
2nd Author's Affiliation Nagoya Institute of Technology(NIT)
3rd Author's Name Toramatsu Shintani
3rd Author's Affiliation Nagoya Institute of Technology(NIT)
Date 2017-11-24
Paper # AI2017-14
Volume (vol) vol.117
Number (no) AI-326
Page pp.pp.43-48(AI),
#Pages 6
Date of Issue 2017-11-17 (AI)