Automatic Term Recognition Method for Military Domain
Ani Song, Xiaoxia Jia, Wei Jiang · Journal of Physics Conference Series · 2021
Abstract With the development of military intelligence, higher requirements are put forward for automatic term recognition in military field. In view of the characteristics of flexible and diverse naming of military requirement documents without annotated corpus, the method of this paper uses the existing military domain core database, and matches the data set and core database by Aho-Corasic algorithm and word segmentation technology, so that the terms to be recognized in the data set can be divided into three types. The possible rules of word formation of military terms are summarized and phrases that conform to the rules of word formation are found in the documents as the term candidate set. The core library and TF-IDF method are used to calculate the value of the candidate terms, and the candidate terms whose value is greater than the threshold are selected iteratively as the real terms. The experimental results show that the F1 value of this method reaches 0.719, which is better than the traditional C-value method. Therefore, the method proposed in this paper can achieve better automatic term recognition effect for military requirement documents without annotation.