Name
Abstract | ||
|---|---|---|
Cross language information retrieval methods are used to determine which segments of Arabic language documents match name-based English queries. We investigate and contrast a word-based translation model with a character-based transliteration model in order to handle spelling variation and previously unseen names. We measure performance by making a novel use of the training data from the 2007 ACE Entity Translation |
Year | DOI | Venue |
|---|---|---|
2009 | 10.1145/1571941.1572065 | SIGIR |
Keywords | Field | DocType |
ace entity translation,training data,word-based translation model,character-based transliteration model,arabic language document,english query,unseen name,cross language information retrieval,cross language name matching,novel use,algorithms,arabic language | Entity linking,Arabic,Information retrieval,Computer science,Language Name,Natural language processing,Universal Networking Language,Artificial intelligence,Spelling,Cross-language information retrieval,Language model,Transliteration | Conference |
Citations | PageRank | References |
3 | 0.69 | 6 |
Authors | ||
1 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| J. Scott Mccarley | 1 | 214 | 21.36 |