Syntree2Vec - An algorithm to augment syntactic hierarchy into word embeddings

TL;DR

Syntree2Vec introduces a graph-based algorithm that incorporates syntactic knowledge into word embeddings, enhancing their syntactic strength and robustness, especially in low-data scenarios.

Contribution

The paper presents a novel algorithm that infuses syntactic hierarchy into word embeddings, improving their performance on domain-specific and limited data.

Findings

Improved syntactic strength of embeddings.

Robust performance on scarce data.

Enhanced domain-specific concept representation.

Abstract

Word embeddings aims to map sense of the words into a lower dimensional vector space in order to reason over them. Training embeddings on domain specific data helps express concepts more relevant to their use case but comes at a cost of accuracy when data is less. Our effort is to minimise this by infusing syntactic knowledge into the embeddings. We propose a graph based embedding algorithm inspired from node2vec. Experimental results have shown that our algorithm improves the syntactic strength and gives robust performance on meagre data.