Name
Abstract | ||
|---|---|---|
We propose a translation selection system based on the vector space model. When each translation candidate of a word is given as a pair of expressions containing the word and its translation, selecting the translation of the word can be considered equivalent to selecting the expression having the most similar context among candidate expressions. The proposed method expresses the context information in "context vectors" constructed from content words co-occurring with the target word. Context vectors represent detailed information composed of lexical attributes (word forms, semantic codes, etc.) and syntactic relations (syntactic dependency, etc.) of the co-occurring words. We tested the proposed method with the Senseval-2 Japanese translation task. Precision/recall was 45.8% to the gold standard in the experiment with the evaluation set. |
Year | Venue | Keywords |
|---|---|---|
2001 | SENSEVAL@ACL | atr-slt system,translation candidate,context information,co-occurring word,senseval-2 japanese translation task,context vector,target word,content word,translation selection system,word form |
Field | DocType | Citations |
Rule-based machine translation,Example-based machine translation,Expression (mathematics),Computer science,Word error rate,Speech recognition,Artificial intelligence,Transfer-based machine translation,Natural language processing,Vector space model,Recall,Syntax | Conference | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Tadashi Kumano | 1 | 20 | 4.23 |
| Hideki Kashioka | 2 | 380 | 67.59 |
| Hideki Tanaka | 3 | 80 | 15.07 |