[Purpose/significance] The structure function of the academic text refers to the summarization of academic text structure and section function. While few of existed studies pay attention to the fusion of multi-level structure of academic text, and the traditional methods usually rely on artificial experience to build rules or features. After the analysis of the multi-level structure of academic text, we construct a structure function recognition model based on multi-level fusion.[Method/process] We use the academic text dataset from ScienceDirect for experiment. First, we apply deep learning algorithms to identify the structure function of academic text at different level. Then we employ the voting method to fuse the results from different levels and models.[Result/conclusion] The results show that the performance improved to varying degrees after fusion. The precision, recall and F1 value of the combined results reached 86%, 84% and 84%, respectively. Compared with the traditional machine learning algorithm SVM, the deep learning algorithm has better performance in the task of academic text classification. Finally, we analyze the misclassification of the structure function of academic text and point out the potential application fields and future research directions.
Wang Jiamin
,
Lu Wei
,
Liu Jiawei
,
Cheng Qikai
. Research on Structure Function Recognition of Academic Text Based on Multi-level Fusion[J]. Library and Information Service, 2019
, 63(13)
: 95
-104
.
DOI: 10.13266/j.issn.0252-3116.2019.13.010
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