Additive Compositionality of Word Vectors
Additive compositionality of word embedding models has been studied from empirical and theoretical perspectives. Existing research on justifying additive compositionality of existing word embedding models requires a rather strong assumption of uniform word distribution. In this paper, we relax that assumption and propose more realistic conditions for proving additive compositionality, and we develop a novel word and sub-word embedding model that satisfies additive compositionality under those conditions. We then empirically show our model{'}s improved semantic representation performance on word similarity and noisy sentence similarity.
Code (0)
등록된 구현이 없습니다.
Tasks
SentenceSentence SimilarityWord SimilaritySimilar Papers 제목 키워드 기반
Skip-Gram − Zipf + Uniform = Vector Additivity
In recent years word-embedding models have gained great popularity due to their remarkable performance on several tasks, including word analogy questions and caption generation. An unexpected {``}side-effect{''} of such …
Caption GenerationDimensionality ReductionWord EmbeddingsRevisiting Additive Compositionality: AND, OR and NOT Operations with Word Embeddings
It is well-known that typical word embedding methods such as Word2Vec and GloVe have the property that the meaning can be composed by adding up the embeddings (additive compositionality). Several theories have been propo…
Word EmbeddingsRevisiting Additive Compositionality: AND, OR, and NOT Operations with Word Embeddings
It is well-known that typical word embedding methods have the property that the meaning can be composed by adding up the embeddings (additive compositionality). Several theories have been proposed to explain additive com…
Word EmbeddingsThe Mechanism of Additive Composition
Additive composition (Foltz et al, 1998; Landauer and Dumais, 1997; Mitchell and Lapata, 2010) is a widely used method for computing meanings of phrases, which takes the average of vector representations of the constitue…
mwetoolkit+sem: Integrating Word Embeddings in the mwetoolkit for Semantic MWE Processing
This paper presents mwetoolkit+sem: an extension of the mwetoolkit that estimates semantic compositionality scores for multiword expressions (MWEs) based on word embeddings. First, we describe our implementation of vecto…
Word Embeddings