TAKE Scientist's Workbench: Semantic Search and Citation-Based Visual Navigation in Scholar Papers

Semantic Computing(2010)

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摘要
We report on recent advances in the project TAKE on the Scientist's Workbench, a platform demonstrating the use of natural language processing (NLP) to support scientists or other knowledge workers in fast and better access to digital document content. We focus on sentence-wise NLP analysis of electronically available scientific paper texts. With the generated NLP annotations, we are able to provide two important, novel applications, (1) robust semantic search in paper content and (2) document navigation based on citation classification. In contrast to previous work, we now provide semantic search on the full textual content of scientific papers instead of just abstracts and use a fall-back strategy to maximize NLP robustness on every sentence. We extend the workbench with a novel visualization and navigation facility that aims at helping scientists to quickly adapt to research fields and topics. It is based on NLP-assisted classification of citation sentences to compute a browsable, typed citation graph.
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关键词
citation classification,full textual content,citation sentence,nlp-assisted classification,nlp annotation,citation graph,sentence-wise nlp analysis,digital document content,semantic search,nlp robustness,paper content,citation-based visual navigation,scholar papers,data mining,indexes,natural language processing,parsing,citation analysis,semantics,robustness,hpsg,accuracy,nlp,visualization,navigation
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