Open AccessAutomatic Text Summarization for Marine Natural Products Literature
Author(s) -
Xukai Zhang,
Sue Min Liu
Publication year - 2021
Publication title -
journal of physics. conference series
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.21
H-Index - 85
eISSN - 1742-6596
pISSN - 1742-6588
DOI - 10.1088/1742-6596/1732/1/012047
Subject(s) - automatic summarization , computer science , encoder , coding (social sciences) , word (group theory) , natural language processing , sequence (biology) , natural (archaeology) , information retrieval , product (mathematics) , artificial intelligence , data mining , linguistics , history , statistics , philosophy , geometry , mathematics , archaeology , biology , genetics , operating system
Based on the Encoder-Decoder framework, an automatic summarization model MNPAS for marine natural products literature is proposed. Instead of directly using the structure of the common encoder in the past, a certain degree of innovation has been made to make Gru model complete the coding work. This advantage is that data information is not so easy to lose. In decoder, attention mechanism is integrated to improve the quality of predicted output word sequence. Compared with the traditional methods, the method proposed in this paper can complete the automatic generation of marine natural product literature abstracts better.