Cross-media analysis and reasoning： advances and directions

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,...

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Bibliographic Details
Published in:Frontiers of information technology & electronic engineering 2017, Vol.18 (1), p.44-57
Main Authors: 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
Format: Article
Language:English
Subjects:
Artificial intelligence
Brain
Communications Engineering
Computer Hardware
Computer Science
Computer Systems Organization and Communication Networks
Computers
Correlation analysis
Datasets
Electrical Engineering
Electronics and Microelectronics
Instrumentation
Knowledge
Knowledge representation
Multimedia
Networks
Reasoning
Review
Semantics
State of the art
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Summary: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.
ISSN:2095-9184
2095-9230
DOI:10.1631/FITEE.1601787