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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 4 of 4 1 ArguminSci: a tool for analyzing argumentation and rhetorical aspects in scientific writing Glavaš, Goran; Lauscher, Anne; Eckert, Kai. - : Association for Computational Linguistics, 2018 BASE Show details 2 Investigating the role of argumentation in the rhetorical analysis of scientific publications with neural multi-task learning models Ponzetto, Simone Paolo; Eckert, Kai; Lauscher, Anne. - : Association for Computational Linguistics, 2018 BASE Show details 3 University of Mannheim @ CLSciSumm-17: Citation-Based Summarization of Scientific Articles Using Semantic Textual Similarity Eckert, Kai; Glavaš, Goran; Lauscher, Anne. - : RWTH, 2017 BASE Show details 4 Usage-driven Maintenance of Knowledge Organization Systems Eckert, Kai. - : Universität Mannheim, 2012 Abstract: Knowledge Organization Systems (KOS) are typically used as background knowledge for document indexing in information retrieval. They have to be maintained and adapted constantly to reflect changes in the domain and the terminology. In this thesis, approaches are provided that support the maintenance of hierarchical knowledge organization systems, like thesauri, classifications, or taxonomies, by making information about the usage of KOS concepts available to the maintainer. The central contribution is the ICE-Map Visualization, a treemap-based visualization on top of a generalized statistical framework that is able to visualize almost arbitrary usage information. The proper selection of an existing KOS for available documents and the evaluation of a KOS for different indexing techniques by means of the ICE-Map Visualization is demonstrated. For the creation of a new KOS, an approach based on crowdsourcing is presented that uses feedback from Amazon Mechanical Turk to relate terms hierarchically. The extension of an existing KOS with new terms derived from the documents to be indexed is performed with a machine-learning approach that relates the terms to existing concepts in the hierarchy. The features are derived from text snippets in the result list of a web search engine. For the splitting of overpopulated concepts into new subconcepts, an interactive clustering approach is presented that is able to propose names for the new subconcepts. The implementation of a framework is described that integrates all approaches of this thesis and contains the reference implementation of the ICE-Map Visualization. It is extendable and supports the implementation of evaluation methods that build on other evaluations. Additionally, it supports the visualization of the results and the implementation of new visualizations. An important building block for practical applications is the simple linguistic indexer that is presented as minor contribution. It is knowledge-poor and works without any training. This thesis applies computer science approaches in the domain of information science. The introduction describes the foundations in information science; in the conclusion, the focus is set on the relevance for practical applications, especially regarding the handling of different qualities of KOSs due to automatic and semiautomatic maintenance. Keyword: 004 Informatik URL: https://madoc.bib.uni-mannheim.de/31754/ https://ub-madoc.bib.uni-mannheim.de/31754 https://madoc.bib.uni-mannheim.de/31754/2/dissertation-eckert.pdf BASE Hide details

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