Name
Title | ||
|---|---|---|
Story embedding: Learning distributed representations of stories based on character networks. |
Abstract | ||
|---|---|---|
•This study proposes novel models and methods for representing stories of narrative works.•The proposed methods focus on synchronizing the story which is latent under various data sources from narrative multimedia.•Through synchronizing scenes in the text and video, stories of the narrative work are discretized.•Names and faces of characters are synchronized by their occurrence distributions on the text and video.•Existing character networks are integrated for better analytics and understanding. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.artint.2020.103235 | Artificial Intelligence |
Keywords | Field | DocType |
Character network,Story analytics,Computational narrative,Story embedding,Story2Vec | Adjacency list,Social network,Embedding,Graph embedding,Static structure,Narrative,Theoretical computer science,Artificial intelligence,Machine learning,Mathematics | Journal |
Volume | Issue | ISSN |
281 | 1 | 0004-3702 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| O.-Joun Lee | 1 | 36 | 7.98 |
| Jason J. Jung | 2 | 1451 | 135.51 |