A Novel Bilingual Word Embedding Method for Lexical Translation Using Bilingual Sense Clique
Most of the existing methods for bilingual word embedding only consider shallow context or simple co-occurrence information. In this paper, we propose a latent bilingual sense unit (Bilingual Sense Clique, BSC), which is derived from a maximum complete sub-graph of pointwise mutual information based graph over bilingual corpus. In this way, we treat source and target words equally and a separated bilingual projection processing that have to be used in most existing works is not necessary any more. Several dimension reduction methods are evaluated to summarize the BSC-word relationship. The proposed method is evaluated on bilingual lexicon translation tasks and empirical results show that bilingual sense embedding methods outperform existing bilingual word embedding methods.
Code (0)
등록된 구현이 없습니다.
Tasks
Dimensionality ReductionTranslationSimilar Papers 제목 키워드 기반
Learning Bilingual Word Embeddings Using Lexical Definitions
Bilingual word embeddings, which representlexicons of different languages in a shared em-bedding space, are essential for supporting se-mantic and knowledge transfers in a variety ofcross-lingual NLP tasks. Existing appr…
TranslationWord AlignmentWord EmbeddingsBilBOWA: Fast Bilingual Distributed Representations without Word Alignments
We introduce BilBOWA (Bilingual Bag-of-Words without Alignments), a simple and computationally-efficient model for learning bilingual distributed representations of words which can scale to large monolingual datasets and…
Cross-Lingual Document ClassificationDocument ClassificationGeneral ClassificationSentence+1Evaluating bilingual word embeddings on the long tail
Bilingual word embeddings are useful for bilingual lexicon induction, the task of mining translations of given words. Many studies have shown that bilingual word embeddings perform well for bilingual lexicon induction bu…
Bilingual Lexicon InductionMachine TranslationWord EmbeddingsBilingual Distributed Word Representations from Document-Aligned Comparable Data
We propose a new model for learning bilingual word representations from non-parallel document-aligned data. Following the recent advances in word representation learning, our model learns dense real-valued word vectors, …
Representation LearningSentenceTranslationWord EmbeddingsThe CQC Algorithm: Cycling in Graphs to Semantically Enrich and Enhance a Bilingual Dictionary
Bilingual machine-readable dictionaries are knowledge resources useful in many automatic tasks. However, compared to monolingual computational lexicons like WordNet, bilingual dictionaries typically provide a lower amoun…
TAGTranslation