論 文Papers

CONFERENCE (INTERNATIONAL)

Multimodal Content-Aware Image Thumbnailing

Kohei Yamamoto (The University of Tokyo), Hayato Kobayashi, Yukihiro Tagami, Hideki Nakayama (The University of Tokyo)

WWW 2016 (The 25th International Conference on World Wide Web) Posters, 2016/4

Category:

自然言語処理 (Natural Language Processing) 画像処理 (Image Processing) 機械学習 (Machine Learning)

Abstract:
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.

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