Abstract
High quality bilingual dictionaries are rarely available for lower-density language pairs, especially for those that are closely related. Using a third language as a pivot to link two other languages is a wellknown solution, and usually requires only two input bilingual dictionaries to automatically induce the new one. This approach, however, produces many incorrect translation pairs because the dictionary entries are normally are not transitive due to polysemy and the ambiguous words in the pivot language. Utilizing the complete structures of the input bilingual dictionaries positively influences the result since dropped meanings can be countered. Moreover, an additional input dictionary may provide more complete information for calculating the semantic distance between word senses which is key to suppressing wrong sense matches. This paper proposes an extended constraint optimization model to inducing new dictionaries of closely related languages from multiple input dictionaries, and its formalization based on Integer Linear Programming. Evaluations indicated that the proposal not only outperforms the baseline method, but also shows improvements in performance and scalability as more dictionaries are utilized.
| Original language | English |
|---|---|
| Pages (from-to) | 221-234 |
| Number of pages | 14 |
| Journal | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
| Volume | 8862 |
| DOIs | |
| Publication status | Published - 2014 Jan 1 |
| Externally published | Yes |
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Keywords
- Bilingual dictionary induction
- Constraint satisfaction
- Pseudo-boolean optimization
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Pivot-based bilingual dictionary extraction from multiple dictionary resources. / Wushouer, Mairidan; Lin, Donghui; Ishida, Toru; Hirayama, Katsutoshi.
In: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), Vol. 8862, 01.01.2014, p. 221-234.Research output: Contribution to journal › Article
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TY - JOUR
T1 - Pivot-based bilingual dictionary extraction from multiple dictionary resources
AU - Wushouer, Mairidan
AU - Lin, Donghui
AU - Ishida, Toru
AU - Hirayama, Katsutoshi
PY - 2014/1/1
Y1 - 2014/1/1
N2 - High quality bilingual dictionaries are rarely available for lower-density language pairs, especially for those that are closely related. Using a third language as a pivot to link two other languages is a wellknown solution, and usually requires only two input bilingual dictionaries to automatically induce the new one. This approach, however, produces many incorrect translation pairs because the dictionary entries are normally are not transitive due to polysemy and the ambiguous words in the pivot language. Utilizing the complete structures of the input bilingual dictionaries positively influences the result since dropped meanings can be countered. Moreover, an additional input dictionary may provide more complete information for calculating the semantic distance between word senses which is key to suppressing wrong sense matches. This paper proposes an extended constraint optimization model to inducing new dictionaries of closely related languages from multiple input dictionaries, and its formalization based on Integer Linear Programming. Evaluations indicated that the proposal not only outperforms the baseline method, but also shows improvements in performance and scalability as more dictionaries are utilized.
AB - High quality bilingual dictionaries are rarely available for lower-density language pairs, especially for those that are closely related. Using a third language as a pivot to link two other languages is a wellknown solution, and usually requires only two input bilingual dictionaries to automatically induce the new one. This approach, however, produces many incorrect translation pairs because the dictionary entries are normally are not transitive due to polysemy and the ambiguous words in the pivot language. Utilizing the complete structures of the input bilingual dictionaries positively influences the result since dropped meanings can be countered. Moreover, an additional input dictionary may provide more complete information for calculating the semantic distance between word senses which is key to suppressing wrong sense matches. This paper proposes an extended constraint optimization model to inducing new dictionaries of closely related languages from multiple input dictionaries, and its formalization based on Integer Linear Programming. Evaluations indicated that the proposal not only outperforms the baseline method, but also shows improvements in performance and scalability as more dictionaries are utilized.
KW - Bilingual dictionary induction
KW - Constraint satisfaction
KW - Pseudo-boolean optimization
UR - http://www.scopus.com/inward/record.url?scp=84911909033&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84911909033&partnerID=8YFLogxK
U2 - 10.1007/978-3-319-13560-1
DO - 10.1007/978-3-319-13560-1
M3 - Article
AN - SCOPUS:84911909033
VL - 8862
SP - 221
EP - 234
JO - Lecture Notes in Computer Science
JF - Lecture Notes in Computer Science
SN - 0302-9743
ER -