LitStoryTeller: An Interactive System for Visual Exploration of Scientific Papers Leveraging Named entities and Comparative Sentences
August 07, 2017 Β· Declared Dead Β· π International Conference on Scientometrics and Informetrics
"No code URL or promise found in abstract"
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Authors
Qing Ping, Chaomei Chen
arXiv ID
1708.02214
Category
cs.HC: Human-Computer Interaction
Cross-listed
cs.CL,
cs.DL
Citations
1
Venue
International Conference on Scientometrics and Informetrics
Last Checked
4 months ago
Abstract
The present study proposes LitStoryTeller, an interactive system for visually exploring the semantic structure of a scientific article. We demonstrate how LitStoryTeller could be used to answer some of the most fundamental research questions, such as how a new method was built on top of existing methods, based on what theoretical proof and experimental evidences. More importantly, LitStoryTeller can assist users to understand the full and interesting story a scientific paper, with a concise outline and important details. The proposed system borrows a metaphor from screen play, and visualizes the storyline of a scientific paper by arranging its characters (scientific concepts or terminologies) and scenes (paragraphs/sentences) into a progressive and interactive storyline. Such storylines help to preserve the semantic structure and logical thinking process of a scientific paper. Semantic structures, such as scientific concepts and comparative sentences, are extracted using existing named entity recognition APIs and supervised classifiers, from a scientific paper automatically. Two supplementary views, ranked entity frequency view and entity co-occurrence network view, are provided to help users identify the "main plot" of such scientific storylines. When collective documents are ready, LitStoryTeller also provides a temporal entity evolution view and entity community view for collection digestion.
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