Enhanced Services for Targeted Information Retrieval by Event Extraction and Data Mining

Authors:
Felix Jungermann;Katharina Morik
Affiliations:
Artificial Intelligence Unit, TU Dortmund,;Artificial Intelligence Unit, TU Dortmund,
Venue:
NLDB '08 Proceedings of the 13th international conference on Natural Language and Information Systems: Applications of Natural Language to Information Systems
Year:
2008

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YALE: rapid prototyping for complex data mining tasks

Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining

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Abstract

We present a framework combining information retrieval with machine learning and (pre-)processing for named entity recognition in order to extract events from a large document collection. The extracted events become input to a data mining component which delivers the final output to specific user's questions. Our case study is the public collection of minutes of plenary sessions of the German parliament and of petitions to the German parliament.