Name
Abstract | ||
|---|---|---|
Creating good visualizations for ordinary users is hard, even with the help of the state-of-the-art interactive data visualization tools, such as Tableau, Qlik, because they require the users to understand the data and visualizations very well. DeepEye is an innovative visualization system that aims at helping everyone create good visualizations simply like a Google search. Given a dataset and a keyword query, DeepEye understands the query intent, generates and ranks good visualizations. The user can pick the one she likes and do a further faceted navigation to easily navigate the candidate visualizations. In this demonstration, the attendees will have the opportunity to experience the following features: (1) visualization recommendation -- Our system can automatically recommends meaningful visualizations by learning from existing known datasets and good visualizations; (2) keyword search -- The attendee can pose text queries for specifying what visualizations she wants (e.g., trends) without specifying how to generate them; (3) faceted navigation -- One can further refine the results by a click-based faceted navigation to find other relevant and interesting visualizations.
|
Year | DOI | Venue |
|---|---|---|
2018 | 10.1145/3183713.3193545 | SIGMOD/PODS '18: International Conference on Management of Data
Houston
TX
USA
June, 2018 |
Field | DocType | ISSN |
Data visualization,Information retrieval,Visualization,Computer science,Keyword search,Database | Conference | 0730-8078 |
ISBN | Citations | PageRank |
978-1-4503-4703-7 | 12 | 0.52 |
References | Authors | |
9 | 5 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Yuyu Luo | 1 | 76 | 10.07 |
| Xuedi Qin | 2 | 67 | 5.59 |
| Nan Tang | 3 | 954 | 59.62 |
| Guoliang Li | 4 | 3077 | 154.70 |
| Xinran Wang | 5 | 12 | 0.52 |