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We propose two new bilingual topic models to better capture the semantic information of each word while discriminating the multiple translations in a noisy ...
Dec 21, 2016 · Title:Inverted Bilingual Topic Models for Lexicon Extraction from Non-parallel Data. Authors:Tengfei Ma, Tetsuya Nasukawa. View a PDF of the ...
We adopt the inverted indexing technique to extend the scope of topic models to the task of lexicon extraction from non-parallel data. • We extend the classical ...
A new bilingual topic models to better capture the semantic information of each word while discriminating the multiple translations in a noisy seed ...
Aug 19, 2017 · Topic models have been successfully applied in lexicon extraction. However, most previous methods are limited to document-aligned data.
To solve these two challenges, we propose two new bilingual topic models to better capture the semantic information of each word while discriminating the ...
TL;DR: This article proposed two new bilingual topic models to better capture the semantic information of each word while discriminating the multiple ...
To solve these two challenges, we propose two new bilingual topic models to better capture the semantic information of each word while discriminating the ...
Bibliographic details on Inverted Bilingual Topic Models for Lexicon Extraction from Non-parallel Data.
Abstract Topic models have been successfully applied in lexicon extraction. However, most previous methods are limited to document-aligned data.