| 大会名称 |
| 2020年 総合大会 |
| 大会コ－ド |
| 2020G |
| 開催年 |
|
2020
|
| 発行日 |
|
2020-03-03
|
| セッション番号 |
|
BS-1
|
| セッション名 |
|
In-Network Intelligence for Design, Management, and Control of Future Networks and Services
|
| 講演日 |
|
2020/3/20
|
| 講演場所(会議室等) |
|
工学部 講義棟１F 104講義室
|
| 講演番号 |
|
BS-1-23
|
| タイトル |
|
A Point-of-Interest Recommendation Model with Multiple Side Information
|
| 著者名 |
|
◎Qizhi Ma, Mutsumi Suganuma, Wataru Kameyama,
|
| キーワード |
|
point-of-interest (POI) recommendation, non-negative matrix factorization (NMF), side information
|
| 抄録 |
|
How to make recommendation for users by using available information is a hot research topic. In this paper, we investigate the point-of-interest (POI) recommendation and propose a model based on non-negative matrix factorization (NMF) with multiple side information to improve the performance. We confirm that adopting multiple side information, including category preference of users, geographical information and friend-relation of users improve the performance of model and propose a new way utilizing the distances in recommendation.
|
| 本文pdf |
|
PDF download
|
