基于人工智能的跨媒体感知与分析技术研究

随着新媒体技术的飞速发展,传统方法已难以准确表达具有人工智能属性的复杂知识结构,跨媒体成为大家关注的焦点。当前,媒体数据感知与分析已经从文本、语音、图像以及视频等单一媒体形态向覆盖网络空间与物理空间的跨媒体融合转变。研究满足新一代人工智能发展规划的跨媒体感知和分析技术体系,并依托知识图谱、长短时记忆网络以及卷积神经网络等技术,实现多通道网络数据爬取、实体统一表征、文本语义识别以及视图像分类等,可有效支撑舆情分析、新闻追踪以及情报获取等领域的跨媒体应用。

Cross-Media Perception and Analysis Technology based on Artificial Intelligence

With the rapid development of new media technology,traditional methods have been difficult to accurately express the complex knowledge structure with artificial intelligence attributes,and cross-media has become the focus of everyone’s attention.Media data perception and analysis has shifted from a single media form such as text,voice,image,and video to a cross-media fusion that covers cyberspace and physical space.Research on the cross-media sensing and analysis technology system that meets the new-generation artificial intelligence development plan,and relying on technologies such as knowledge atlas,long-and short-term memory networks,and convolutional neural networks,to achieve multi-channel network data crawling,unified entity representation,text semantic recognition,and visual image classification,etc.,can effectively support cross-media applications in the areas of public opinion analysis,news tracking,and information acquisition.