跨媒体分析与推理:研究进展与发展方向（英文）

被引：49

作者：

Yuxin PENG ^{[1
]}

Wenwu ZHU ^{[2
]}

Yao ZHAO ^{[3
]}

Changsheng XU ^{[4
]}

Qingming HUANG ^{[5
]}

Hanqing LU ^{[4
]}

Qinghua ZHENG ^{[6
]}

Tiejun HUANG ^{[7
]}

Wen GAO ^{[7
]}

机构：

[1] Institute of Computer Science and Technology,Peking University

[2] Department of Computer Science and Technology,Tsinghua University

[3] Institute of Information Science,Beijing Jiaotong University

[4] National Laboratory of Pattern Recognition,Institute of Automation,Chinese Academy of Sciences

[5] Key Laboratory of Intelligent Information Processing,Institute of Computing Technology,Chinese Academy of Sciences

[6] Department of Computer Science and Technology,Xi'an Jiaotong University

[7] School of Electronics Engineering and Computer Science,Peking

来源：

Frontiers of Information Technology & Electronic Engineering | 2017年 / 18卷 / 01期

关键词：

跨媒体分析; 跨媒体推理; 跨媒体应用;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

跨媒体分析与推理是计算机科学的热点问题,也是人工智能中一个具有广阔前景的研究方向。目前,尚未有文献对跨媒体分析与推理的现有方法进行归纳总结并给出它的研究进展、挑战及发展方向。为解决这些问题,本文从七个方面进行综述:(1)跨媒体统一表征理论与模型;(2)跨媒体关联理解与深度挖掘;(3)跨媒体知识图谱构建与学习方法;(4)跨媒体知识演化与推理;(5)跨媒体描述与生成;(6)跨媒体智能引擎;(7)跨媒体智能应用。本文的目标是给出跨媒体分析与推理的方法、进展以及发展方向,吸引更多人关注该领域的最新进展,通过探讨面临的挑战和研究方向,为研究者提供重要参考。

引用

页码：44 / 58

页数：15

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