Papers by Christopher Tauchmann
Beyond Generic Summarization: A Multi-faceted Hierarchical Summarization Corpus of Large Heterogeneous Data (L18-1)
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| Challenge: | Automated summarization has focused on ten to twenty documents, typically news articles, but could in theory analyze hundreds of documents from a wide range of sources and provide an overview to the interested reader. |
| Approach: | They propose a method for creating hierarchical summarization corpora from large, heterogeneous document collections by crowdsourcing relevant content and asking trained annotators to order the relevant information hierarchically. |
| Outcome: | The proposed method can be used to develop and evaluate hierarchical summarization systems. |
ArgumenText: Searching for Arguments in Heterogeneous Sources (N18-5)
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Christian Stab, Johannes Daxenberger, Chris Stahlhut, Tristan Miller, Benjamin Schiller, Christopher Tauchmann, Steffen Eger, Iryna Gurevych
| Challenge: | Argument mining is a core technology for enabling argument search in large corpora . but current methods fail when applied to heterogeneous texts . despite its obvious applications, argument search has attracted relatively little attention . |
| Approach: | They propose a system that searches sentential arguments for any given topic . ArgumenText automatically identifies and classifies arguments by relevance . |
| Outcome: | The proposed system covers 89% of arguments found in expert-curated lists . it also identifies additional valid arguments omitted or overlooked by human curators . |
Language Agnostic Automatic Summarization Evaluation (2020.lrec-1)
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| Challenge: | Existing evaluation methods for summarization of documents have been primarily focused on the English language. |
| Approach: | They propose to use ROUGE and PYRAMID to evaluate non-English data using English and non- English data sets. |
| Outcome: | The proposed evaluation methods can be adapted to non-English data, and the results show that they can perform well on non- English data. |