Graph-based Arabic text semantic representation

作者：

Highlights：

• Semantic representation of Arabic text can facilitate several natural language processing applications such as text summarization and textual entailment.

• A graph-based Arabic text semantic representation model were used to represent the meaning of Arabic sentences as a rooted acyclic graph.

• The proposed representation model was evaluated according to its ability to enhance Arabic Textual Entailment recognition.

• Arabic Textual Entailment Dataset (ArbTED) was used in the experiments, and the results showed the proposed model enhanced the performance of Arabic textual entailment recognition.

摘要

•Semantic representation of Arabic text can facilitate several natural language processing applications such as text summarization and textual entailment.•A graph-based Arabic text semantic representation model were used to represent the meaning of Arabic sentences as a rooted acyclic graph.•The proposed representation model was evaluated according to its ability to enhance Arabic Textual Entailment recognition.•Arabic Textual Entailment Dataset (ArbTED) was used in the experiments, and the results showed the proposed model enhanced the performance of Arabic textual entailment recognition.

论文关键词：Knowledge representation,Semantic graph,Semantic representation,Textual entailment,Arabic natural language processing,ArbTED

论文评审过程：Received 26 June 2019, Revised 13 December 2019, Accepted 14 December 2019, Available online 27 December 2019, Version of Record 27 December 2019.

论文官网地址：https://doi.org/10.1016/j.ipm.2019.102183