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Front. Inform. Technol. Electron. Eng.  2017, Vol. 18 Issue (1): 44-57    DOI: 10.1631/FITEE.1601787
Review Articles     
Cross-media analysis and reasoning: advances and directions
Yu-xin Peng, Wen-wu Zhu, Yao Zhao, Chang-sheng Xu, Qing-ming Huang, Han-qing Lu, Qing-hua Zheng, Tie-jun Huang, Wen Gao
Institute of Computer Science and Technology, Peking University, Beijing 100871, China; Department of Computer Science and Technology, Tsinghua University, Beijing 100084, China; Institute of Information Science, Beijing Jiaotong University, Beijing 100044, China; National Laboratory of Pattern Recognition, Institute of Automation, Chinese Academy of Sciences, Beijing 100190, China; Key Laboratory of Intelligent Information Processing, Institute of Computing Technology, Chinese Academy of Sciences, Beijing 100190, China; Department of Computer Science and Technology, Xi'an Jiaotong University, Xi'an 710049, China; School of Electronics Engineering and Computer Science, Peking University, Beijing 100871, China
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Abstract  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.

Key wordsCross-media analysis      Cross-media reasoning      Cross-media applications     
Received: 07 December 2016      Published: 20 January 2017
CLC:  TP391  
Cite this article:

Yu-xin Peng, Wen-wu Zhu, Yao Zhao, Chang-sheng Xu, Qing-ming Huang, Han-qing Lu, Qing-hua Zheng, Tie-jun Huang, Wen Gao. Cross-media analysis and reasoning: advances and directions. Front. Inform. Technol. Electron. Eng., 2017, 18(1): 44-57.

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http://www.zjujournals.com/xueshu/fitee/10.1631/FITEE.1601787     OR     http://www.zjujournals.com/xueshu/fitee/Y2017/V18/I1/44

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