Abstract

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 advantages of advanced text mining algorithms for creating a comprehensive media analysis.

@inproceedings{PlochLommatzschSchultze:AnAdvancedPressReviewSystemCombiningDeepNewsAnalysisAndMachineLearningAlgorithms,
author = {Danuta Ploch and Andreas Lommatzsch and Florian  Schultze},
title = {An Advanced Press Review System Combining Deep News Analysis and Machine Learning Algorithms},
booktitle = {Proc. of the 54h  Annual meeting of the Association for Computational Linguistics (ACL), Berlin, Germany},
year = {2016},
series = {ACL '16},
pages = {109-114},
isbn = {ISBN 978-1-945626-03-6},
location = {Berlin, Germany},
publisher = {Association for Computational Linguistics},
address = {Stroudsburg, PA 18360, USA},
}