Daoxu Chen


2018

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Enriching Word Embeddings with Domain Knowledge for Readability Assessment
Zhiwei Jiang | Qing Gu | Yafeng Yin | Daoxu Chen
Proceedings of the 27th International Conference on Computational Linguistics

In this paper, we present a method which learns the word embedding for readability assessment. For the existing word embedding models, they typically focus on the syntactic or semantic relations of words, while ignoring the reading difficulty, thus they may not be suitable for readability assessment. Hence, we provide the knowledge-enriched word embedding (KEWE), which encodes the knowledge on reading difficulty into the representation of words. Specifically, we extract the knowledge on word-level difficulty from three perspectives to construct a knowledge graph, and develop two word embedding models to incorporate the difficulty context derived from the knowledge graph to define the loss functions. Experiments are designed to apply KEWE for readability assessment on both English and Chinese datasets, and the results demonstrate both effectiveness and potential of KEWE.

2015

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A Graph-based Readability Assessment Method using Word Coupling
Zhiwei Jiang | Gang Sun | Qing Gu | Tao Bai | Daoxu Chen
Proceedings of the 2015 Conference on Empirical Methods in Natural Language Processing