推动网络新闻业务的质量水平:基于语义的国际新闻出版内容检索与合成

M. Schranz
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引用次数: 1

摘要

电子出版利用了许多可能性来展示或交换信息,并通过最流行的媒体如因特网进行交流。通过利用现代Web技术,如Web服务、松耦合服务和点对点网络,我们描述了智能商业新闻表示和分发网络的集成。使用语义技术可以在可扩展的国际层面上耦合多国和多语言商业新闻数据,从而引入迄今为止新闻分发领域的替代技术无法实现的服务质量。在体系结构上,我们将现有服务的松散耦合确定为解决多国和多语言新闻呈现和分发网络的最可行方法。此外,我们通过使用向量空间模型等人工智能技术将跨国新闻内容关联起来,从而在语义上丰富它们。在总结经验的基础上,阐述了语义学与传播技术的技术融合,以构建现代国际新闻网络。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Pushing the Quality Level in Networked News Business: Semantic-Based Content Retrieval and Composition in International News Publishing
Electronic publishing exploits numerous possibilities to present or exchange information and to communicate via most current media like the Internet. By utilizing modern Web technologies like Web Services, loosely coupled services, and peer-to-peer networks we describe the integration of an intelligent business news presentation and distribution network. Employing semantics technologies enables the coupling of multinational and multilingual business news data on a scalable international level and thus introduce a service quality that is not achieved by alternative technologies in the news distribution area so far. Architecturally, we identified the loose coupling of existing services as the most feasible way to address multinational and multilingual news presentation and distribution networks. Furthermore we semantically enrich multinational news contents by relating them using AI techniques like the Vector Space Model. Summarizing our experiences we describe the technical integration of semantics and communication technologies in order to create a modern international news network.
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