Name
Abstract | ||
|---|---|---|
This abstract paper sketches our research towards Structured Semantic Embedding of multimedia data. Though a tag may have multiple senses with completely different visual imagery, current semantic embedding methods represent the tag by a single vector regardless of its senses. We challenge this convention, arguing the importance of adding semantic structures into semantic embedding. In particular, we develop Hierarchical Semantic Embedding, a simple model that exploits the WordNet hierarchy to make the semantic embedding structured to some extent. We demonstrate the viability of structured semantic embedding for tag disambiguation and zero-shot image tagging. |
Year | DOI | Venue |
|---|---|---|
2015 | 10.1145/2808492.2808577 | ICIMCS |
Field | DocType | Citations |
Semantic technology,Semantic Web Stack,Computer science,Natural language processing,Artificial intelligence,WordNet,Semantic computing,Semantic similarity,Embedding,Information retrieval,Semantic equivalence,Semantic grid,Multimedia | Conference | 0 |
PageRank | References | Authors |
0.34 | 8 | 5 |