Enhanced Services for Targeted Information Retrieval by Event Extraction and Data Mining
| Autor: | Felix Jungermann, Katharina Morik |
|---|---|
| Rok vydání: | 2008 |
| Předmět: |
Information retrieval
Event (computing) Computer science business.industry Parliament media_common.quotation_subject computer.software_genre Relationship extraction language.human_language German Text mining Named-entity recognition Knowledge extraction Component (UML) language Data mining business computer media_common |
| Zdroj: | Lecture Notes in Computer Science ISBN: 9783540698579 NLDB |
| DOI: | 10.1007/978-3-540-69858-6_36 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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