Papers with KEWE

1 papers
Enriching Word Embeddings with Domain Knowledge for Readability Assessment (C18-1)

Copied to clipboard

Challenge: Existing word embedding models focus on syntactic or semantic relations of words, while ignoring reading difficulty.
Approach: They propose a method which learns the word embedding for readability assessment . they extract the knowledge on word-level difficulty from three perspectives to construct a knowledge graph .
Outcome: The proposed method is effective and potential, the authors show . they use the knowledge-enriched word embedding model on English and Chinese datasets .

What is GenGO?

GenGO is an NLP powered publication search system. It currenctly indexes 30k+ papers from ACL Anthology, and implements multi-aspect summarization, semantic search, and more!

Information

About
Limitations