中文摘要：

跨媒介的分析并且推理为人工智能是在计算机科学，和一个有希望的方向的一个活跃研究区域。就我们的知识而言，然而，没有存在工作为跨媒介的分析总结了最先进的方法并且推理或为这个领域的介绍进展，挑战，和未来方向。处理这些问题，我们如下提供概述：(1 ) 为跨媒介的一致表示的理论和模型；(2 ) 跨媒介的关联理解和深采矿；(3 ) 跨媒介的知识图建设和学习方法论；(4 ) 跨媒介的知识进化并且推理；(5 ) 跨媒介的描述和产生；(6 ) 跨媒介的聪明的引擎；并且(7 ) 跨媒介的聪明的应用。由在跨媒介的分析介绍途径，进展，和未来方向并且推理，我们的球门是不仅在这个领域里引起更多的注意到最先进的进展，而且由在这些区域讨论挑战和研究方向提供技术卓见。

英文摘要：

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.