Name
Abstract | ||
|---|---|---|
In our study of Text-to-Scene conversation (TTS), which translates natural language into animations automatically, we realized that event entailment knowledge is useful in generating scenes since the main part of a scene is to show an event. In this paper, we provide some results of our attempt to extract event entailment knowledge. We use entailment chains instead of traditional entailment rules since the sequence of events is a process which make useful in TTS. The result shows that the work is worth to continue to study. |
Year | DOI | Venue |
|---|---|---|
2010 | 10.1109/ICMLC.2010.5580890 | ICMLC |
Keywords | Field | DocType |
text-to-scene conversion,event entailment,natural language,information extraction,computer animation,knowledge acquisition,animations,natural language processing,text analysis,event entailment knowledge extraction,animation,cybernetics,generators,machine learning | Logical consequence,Conversation,Textual entailment,Computer science,Information extraction,Natural language,Artificial intelligence,Animation,Natural language processing,Computer animation,Knowledge acquisition | Conference |
Volume | ISBN | Citations |
3 | 978-1-4244-6526-2 | 0 |
PageRank | References | Authors |
0.34 | 8 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Hanjing Li | 1 | 18 | 5.22 |
| Zhen Li | 2 | 33 | 12.70 |
| Xiaoping Xue | 3 | 186 | 17.00 |
| Tiejun Zhao | 4 | 643 | 102.68 |