| 作成者 |
|
|
|
| 本文言語 |
|
| 出版者 |
|
|
|
| 発行日 |
|
| 会議情報 |
|
| 出版タイプ |
|
| アクセス権 |
|
| 概要 |
Recently, CGM (Consumer Generated Media) services become popular. Although a huge amount of contents have been posted to CGM site, but only a few contents are selected and viewed by users. This phenom...enon are called as very short head and very long tails. Some researcher mentioned that recommendation algorithms made in uence to user's content selection strongly. Serendipitous recommendation is necessary for healthy cultural glowth of CGM contents. In this paper, we propose a new serendipitious recommendation method for CGM novels. We apply clustering to novels to divide into middle size clusters, and contents are similar in the same cluster. For clustering, each content is represented into a vector using doc2vec. Next, we calculate the distance from the user ’s preference (bookmark) to each clusters. We believe that contents in near but not nearest cluster are better for serendipitious recommendation. We apply our method to web CGM novels in syosetu.com, and we also construct a web based recommendation system.続きを見る
|
Mendeley出力
docmas18-iida