Interactive Hierarchical Quote Extraction for Content Insights
| dc.contributor.author | Knittel, Johannes | en_US |
| dc.contributor.author | Koch, Steffen | en_US |
| dc.contributor.author | Ertl, Thomas | en_US |
| dc.contributor.editor | Madeiras Pereira, João and Raidou, Renata Georgia | en_US |
| dc.date.accessioned | 2019-06-02T18:21:09Z | |
| dc.date.available | 2019-06-02T18:21:09Z | |
| dc.date.issued | 2019 | |
| dc.description.abstract | This work presents a new approach to visually summarize large micro-document collections such as tweets. We extract frequent patterns of phrases as shortened quotes to present analysts an overview of popular snippets and statements, enabling more specific insights into large text collections compared to keyword-based visualizations. In our hierarchical structure, each quote can be the starting point to extract more fine-grained patterns on a subset of sentences that match the parent pattern. We show that our approach is scalable by applying it to millions of tweets. | en_US |
| dc.description.sectionheaders | Posters | |
| dc.description.seriesinformation | EuroVis 2019 - Posters | |
| dc.identifier.doi | 10.2312/eurp.20191134 | |
| dc.identifier.isbn | 978-3-03868-088-8 | |
| dc.identifier.pages | 13-15 | |
| dc.identifier.uri | https://doi.org/10.2312/eurp.20191134 | |
| dc.identifier.uri | https://diglib.eg.org:443/handle/10.2312/eurp20191134 | |
| dc.publisher | The Eurographics Association | en_US |
| dc.subject | Human | |
| dc.subject | centered computing | |
| dc.subject | Visual analytics | |
| dc.subject | Computing methodologies | |
| dc.subject | Information extraction | |
| dc.title | Interactive Hierarchical Quote Extraction for Content Insights | en_US |