Multimodal Content-Aware Image Thumbnailing
WWW 2016 (The 25th International Conference on World Wide Web) Posters, 2016/4
自然言語処理 (Natural Language Processing) 画像処理 (Image Processing) 機械学習 (Machine Learning)
- News article recommendation has the key problem of needing to eliminate the redundant information in a ranked list
in order to provide more relevant information within a limited time and space. In this study, we tackle this problem
by using image thumbnailing, which can be regarded as the
summarization of news images. We propose a multimodal
image thumbnailing method considering news text as well
as images themselves. We evaluate this approach on a real
data set based on news articles that appeared on Yahoo!
JAPAN. Experimental results demonstrate the effectiveness
of our proposed method.
Poster Download (3.6MB)
Multimodal Content-Aware Image Thumbnailing（PDF 266KB）