TY - GEN
T1 - A Hybrid Model for Community-Oriented Lexical Simplification
AU - Song, Jiayin
AU - Shen, Yingshan
AU - Lee, John
AU - Hao, Tianyong
PY - 2020/10
Y1 - 2020/10
N2 - Generally, lexical simplification replaces complex words in a sentence with simplified and synonymous words. Most current methods improve lexical simplification by optimizing ranking algorithm and their performance are limited. This paper utilizes a hybrid model through merging candidate words generated by a Context2vec neural model and a Context-aware model based on a weighted average method. The model consists of four steps: candidate word generation, candidate word selection, candidate word ranking, and candidate word merging. Through the evaluation on standard datasets, our hybrid model outperforms a list of baseline methods including Context2vec method, Context-aware method, and the state-of-the-art semantic-context ranking method, indicating its effectiveness in community-oriented lexical simplification task.
AB - Generally, lexical simplification replaces complex words in a sentence with simplified and synonymous words. Most current methods improve lexical simplification by optimizing ranking algorithm and their performance are limited. This paper utilizes a hybrid model through merging candidate words generated by a Context2vec neural model and a Context-aware model based on a weighted average method. The model consists of four steps: candidate word generation, candidate word selection, candidate word ranking, and candidate word merging. Through the evaluation on standard datasets, our hybrid model outperforms a list of baseline methods including Context2vec method, Context-aware method, and the state-of-the-art semantic-context ranking method, indicating its effectiveness in community-oriented lexical simplification task.
KW - Context-aware
KW - Context2vec
KW - Lexical simplification
KW - Context-aware
KW - Context2vec
KW - Lexical simplification
KW - Context-aware
KW - Context2vec
KW - Lexical simplification
UR - http://www.scopus.com/inward/record.url?scp=85093088850&partnerID=8YFLogxK
UR - https://www.scopus.com/record/pubmetrics.uri?eid=2-s2.0-85093088850&origin=recordpage
U2 - 10.1007/978-3-030-60450-9_11
DO - 10.1007/978-3-030-60450-9_11
M3 - RGC 32 - Refereed conference paper (with host publication)
SN - 9783030604493
VL - Part I
T3 - Lecture Notes in Computer Science
SP - 132
EP - 144
BT - Natural Language Processing and Chinese Computing - 9th CCF International Conference, NLPCC 2020, Proceedings
A2 - Zhu, Xiaodan
A2 - Zhang, Min
A2 - Hong, Yu
PB - Springer Nature Switzerland AG
T2 - 9th CCF International Conference on Natural Language Processing and Chinese Computing (NLPCC 2020)
Y2 - 14 October 2020 through 18 October 2020
ER -