A Method for Extracting Keywords from English Literature Based on Location Feature Weighting

摘要

Natural language processing (NLP) is a frontier technology in the field of artificial intelligence. Keywords extraction is a key link in NLP and plays an important role in NLP. TFIDF algorithm is considered as the most important invention in information mining. This paper uses the position characteristics of words in the title and full text in the text, and makes weighted improvement on the basis of TFIDF algorithm to improve the accuracy of keyword extraction. In this paper, 400 articles of ACM were used as the training data set, 40 articles as the test set, and accuracy rate, recall rate and F1 value were used as the evaluation criteria. Experimental data show that this method improves the accuracy of keyword extraction and improves the performance of the original algorithm.