Details

Autor(en) / Beteiligte

• Peng, Yu-xin
• Zhu, Wen-wu
• Zhao, Yao
• Xu, Chang-sheng
• Huang, Qing-ming
• Lu, Han-qing
• Zheng, Qing-hua
• Huang, Tie-jun
• Gao, Wen

Titel

Cross-media analysis and reasoning： advances and directions

Ist Teil von

• Frontiers of information technology & electronic engineering, 2017, Vol.18 (1), p.44-57

Ort / Verlag

Hangzhou: Zhejiang University Press

Erscheinungsjahr

2017

Quelle

Alma/SFX Local Collection

Beschreibungen/Notizen

• Cross-media analysis and reasoning is an active research area in computer science, and a promising direction for artificial intelligence. However, to the best of our knowledge, no existing work has summarized the state-of-the-art methods for cross-media analysis and reasoning or presented advances, challenges, and future directions for the field. To address these issues, we provide an overview as follows： （1） theory and model for cross-media uniform representation; （2） cross-media correlation understanding and deep mining; （3） cross-media knowledge graph construction and learning methodologies; （4） cross-media knowledge evolution and reasoning; （5） cross-media description and generation; （6） cross-media intelligent engines; and （7） cross-media intelligent applications. By presenting approaches, advances, and future directions in cross-media analysis and reasoning, our goal is not only to draw more attention to the state-of-the-art advances in the field, but also to provide technical insights by discussing the challenges and research directions in these areas.