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An Advanced Press Review System Combining Deep News Analysis and Machine Learning Algorithms

机译:结合深度新闻分析和机器学习算法的高级新闻评论系统

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In our media-driven world the perception of companies and institutions in the media is of major importance. The creation of press reviews analyzing the media response to company-related events is a complex and time-consuming task. In this demo we present a system that combines advanced text mining and machine learning approaches in an extensible press review system. The system collects documents from heterogeneous sources and enriches the documents applying different mining, filtering, classification, and aggregation algorithms. We present a system tailored to the needs of the press department of a major German University. We explain how the different components have been trained and evaluated. The system enables us demonstrating the live analyzes of news and social media streams as well as the strengths of advanced text mining algorithms for creating a comprehensive media analysis.
机译:在我们这个以媒体为主导的世界中,媒体对公司和机构的看法至关重要。分析媒体对公司相关事件的回应的媒体评论的创建是一项复杂且耗时的任务。在此演示中,我们介绍了一个在可扩展的新闻评论系统中结合了高级文本挖掘和机器学习方法的系统。该系统从异构来源收集文档,并使用不同的挖掘,过滤,分类和聚合算法来丰富文档。我们提供了根据主要德国大学新闻系的需求量身定制的系统。我们将说明如何培训和评估不同的组件。该系统使我们能够演示新闻和社交媒体流的实时分析,以及用于创建全面媒体分析的高级文本挖掘算法的优势。

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