Enhancing Bilingual Lexicon Induction with Dynamic Translation
The result's identifiers
Result code in IS VaVaI
<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216224%3A14330%2F25%3A00140716" target="_blank" >RIV/00216224:14330/25:00140716 - isvavai.cz</a>
Result on the web
<a href="http://dx.doi.org/10.5220/0013346000003890" target="_blank" >http://dx.doi.org/10.5220/0013346000003890</a>
DOI - Digital Object Identifier
<a href="http://dx.doi.org/10.5220/0013346000003890" target="_blank" >10.5220/0013346000003890</a>
Alternative languages
Result language
angličtina
Original language name
Enhancing Bilingual Lexicon Induction with Dynamic Translation
Original language description
Bilingual lexicon induction (BLI) has been a popular task for evaluating cross-lingual word embeddings (CWEs). The prevalent metric employed in the evaluation is precision at k, where k represents the number of target words retrieved for each source word. However, establishing a fixed k for the entire evaluation dataset proves challenging due to varying target word counts for each source word. This leads to limited results, compromising either precision or recall. In this paper, we present a novel classification-based approach with dynamic k for bilingual lexicon induction that aims to identify all relevant target words for each source word by exploiting the information derived from the aligned embeddings while offering a balanced trade-off between precision and recall. On top of that, it enables the evaluation of the existing CWEs using dynamic k. Compared to the standard baseline systems and evaluation procedures, it provides competitive results.
Czech name
—
Czech description
—
Classification
Type
D - Article in proceedings
CEP classification
—
OECD FORD branch
10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)
Result continuities
Project
—
Continuities
S - Specificky vyzkum na vysokych skolach
Others
Publication year
2025
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Article name in the collection
Proceedings of the 17th International Conference on Agents and Artificial Intelligence - Volume 2: ICAART
ISBN
9789897587375
ISSN
2184-3589
e-ISSN
—
Number of pages
10
Pages from-to
735-744
Publisher name
SciTePress
Place of publication
Porto
Event location
Porto, Portugal
Event date
Jan 1, 2025
Type of event by nationality
WRD - Celosvětová akce
UT code for WoS article
—