The synthesis process of document content and its visualization play a basic role in the context of knowledge representation and retrieval. Existing methods for tag-clouds generations are mostly based on text content of documents, others also consider statistical or semantic information to enrich the document summary, while precious information deriving from multimedia content is often neglected. In this paper we present a document summarization and visualization technique based on both statistical and semantic analysis of textual and visual contents. The result of our framework is a Visual Semantic Tag Cloud based on the highlighting of relevant terms in a document using some features (font size, color, etc.) showing the importance of a term compared to other ones. The semantic information is derived from a knowledge base where concepts are represented through several multimedia items. The Visual Semantic Tag Cloud can be used not only to synthesize a document but also to represent a set of documents grouped by categories using a topic detection technique based on textual and visual analysis of multimedia features. Our work aims at demonstrating that with the help of semantic analysis and the combination of textual and visual features it is possible to improve the user knowledge acquisition by means of a synthesized visualization. The whole strategy has been evaluated by means of a ground truth and compared with similar approaches. Experimental results show the effectiveness of our approach, which outperforms state-of-art algorithms in topic detection combining both visual and semantic information.

文档内容的合成过程及其可视化在知识表示和检索的环境中起着基本作用。用于标记云生成的现有方法主要基于文档的文本内容，其他方法也考虑统计或语义信息来丰富文档摘要，而来自多媒体内容的宝贵信息通常被忽略。在本文中，我们提出了一种基于文本和视觉内容的统计和语义分析的文档摘要和可视化技术。我们框架的结果是一个视觉语义标签云，它基于使用一些功能（字体大小，颜色等）突出显示文档中相关术语的功能，从而显示了一个术语相对于其他术语的重要性。语义信息来自知识库，在知识库中，概念通过几个多媒体项表示。视觉语义标签云不仅可以用于合成文档，还可以使用基于多媒体功能的文本和视觉分析的主题检测技​​术来表示按类别分组的一组文档。我们的工作旨在证明借助语义分析以及文本和视觉功能的组合，可以通过合成可视化来改善用户知识的获取。整个策略已通过基本事实进行了评估，并与类似方法进行了比较。实验结果证明了该方法的有效性，该方法在结合视觉和语义信息的主题检测方面优于最新算法。