Name
Abstract | ||
|---|---|---|
While images of famous people and places are abundant on the Internet, they are much harder to retrieve for less popular entities such as notable computer scientists or regionally interesting churches. Querying the entity names in image search engines yields large candidate lists, but they often have low precision and unsatisfactory recall. In this paper, we propose a principled model for finding images of rare or ambiguous named entities. We propose a set of efficient, light-weight algorithms for identifying entity-specific keyphrases from a given textual description of the entity, which we then use to score candidate images based on the matches of keyphrases in the underlying Web pages. Our experiments show the high precision-recall quality of our approach. |
Year | DOI | Venue |
|---|---|---|
2011 | 10.1145/2063576.2063608 | CIKM |
Keywords | Field | DocType |
popular entity,difficult entity,light-weight algorithm,entity name,famous people,entity-specific keyphrases,score candidate image,large candidate list,long tail,interesting church,image search engines yield,high precision-recall quality,ranking,web pages | Data mining,Search engine,Web page,Information retrieval,Ranking,Computer science,Long tail,Recall,The Internet | Conference |
Citations | PageRank | References |
7 | 0.41 | 18 |
Authors | ||
3 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bilyana Taneva | 1 | 410 | 14.37 |
| Mouna Kacimi | 2 | 257 | 19.82 |
| Gerhard Weikum | 3 | 12710 | 2146.01 |