Name
Abstract | ||
|---|---|---|
This paper presents a method for the hierarchical classification of image galleries into a taxonomy. The proposed method links textual gallery metadata to Wikipedia pages and categories. Entity extraction from metadata, entity ranking, and selection of categories is based on Wikipedia and does not require labeled training data. The resulting system performs well above a random baseline, and achieves a (micro-averaged) F-score of 0.59 on the 9 top categories of the taxonomy and 0.40 when using all 57 categories. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1007/978-3-642-31178-9_20 | NLDB |
Keywords | Field | DocType |
resulting system,entity extraction,wikipedia page,entity ranking,image gallery,textual gallery metadata,top category,hierarchical classification,classifying image gallery,random baseline,wikipedia,taxonomy,classification | Training set,Data mining,Metadata,Information retrieval,Ranking,Computer science,Artificial intelligence,Natural language processing | Conference |
Citations | PageRank | References |
0 | 0.34 | 9 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Gerwin Kramer | 1 | 0 | 0.68 |
| Gosse Bouma | 2 | 483 | 70.88 |
| Dennis Hendriksen | 3 | 0 | 0.34 |
| Mathijs Homminga | 4 | 0 | 0.34 |