TY - GEN
T1 - A heuristic framework for pivot-based bilingual dictionary induction
AU - Wushouer, Mairidan
AU - Ishida, Toru
AU - Lin, Donghui
N1 - Funding Information:
Disclosures: Dr. Hussain, Dr. Sosa, Dr. Ambroggio, and Mrs. Gallagher have nothing to disclose. Patrick Brady reports grants from the Agency for Healthcare Research and Quality, outside the submitted work. The authors certify that this submission is not under review by any other publication. The author team has no conflicts of interest to disclose. Funding: Ms. Hussain was supported by the Society of Hospital Medicine’s Student Hospitalist Scholar Grant Program in 2017. Dr. Brady receives career development support from AHRQ K08-HS023827. The project described was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health, under Award Number 5UL1TR001425-04. The content is solely the responsibility of the authors and does not necessarily represent the official views of the SHM, AHRQ, or NIH.
Funding Information:
Funding: Ms. Hussain was supported by the Society of Hospital Medicine's Student Hospitalist Scholar Grant Program in 2017. Dr. Brady receives career development support from AHRQ K08-HS023827. The project described was supported by the National Center for Advancing Translational Sciences of the National Institutes of Health, under Award Number 5UL1TR001425-04. The content is solely the responsibility of the authors and does not necessarily represent the official views of the SHM, AHRQ, or NIH.
PY - 2013
Y1 - 2013
N2 - High quality machine readable dictionaries are very useful, but such resources are rarely available for lower-density language pairs, especially for those that are closely related. In this paper, we proposed a heuristic framework that aims at inducing one-to-one mapping dictionary of a closely related language pair from available dictionaries where a distant language is involved. The key insight of the framework is the ability to create heuristics by using distant language as pivot, incorporate given heuristics, and an iterative induction mechanism that human interaction can be potentially integrated. An experiment based on basic heuristics regarding syntactics and semantics resulted in up to 85.2% correctness in target dictionary with correctness of major part reached 95.3%, which proved that we can perform automated creation of a high quality dictionary with our framework.
AB - High quality machine readable dictionaries are very useful, but such resources are rarely available for lower-density language pairs, especially for those that are closely related. In this paper, we proposed a heuristic framework that aims at inducing one-to-one mapping dictionary of a closely related language pair from available dictionaries where a distant language is involved. The key insight of the framework is the ability to create heuristics by using distant language as pivot, incorporate given heuristics, and an iterative induction mechanism that human interaction can be potentially integrated. An experiment based on basic heuristics regarding syntactics and semantics resulted in up to 85.2% correctness in target dictionary with correctness of major part reached 95.3%, which proved that we can perform automated creation of a high quality dictionary with our framework.
KW - Dictionary induction
KW - Heuristics
KW - Iterative framework
KW - Pivot language
UR - http://www.scopus.com/inward/record.url?scp=84893252484&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84893252484&partnerID=8YFLogxK
U2 - 10.1109/CultureComputing.2013.27
DO - 10.1109/CultureComputing.2013.27
M3 - Conference contribution
AN - SCOPUS:84893252484
SN - 9780769550473
T3 - Proceedings - 2013 International Conference on Culture and Computing, Culture and Computing 2013
SP - 111
EP - 116
BT - Proceedings - 2013 International Conference on Culture and Computing, Culture and Computing 2013
PB - IEEE Computer Society
T2 - 2013 International Conference on Culture and Computing, Culture and Computing 2013
Y2 - 16 September 2013 through 18 September 2013
ER -