This paper propose a new method to extract ontology concepts from multiple text of the same type. This method uses mutual information and document frequency. According to the mutual information tend to choose the low frequency words, combining mutual information and document frequency to avoid this problem. In this paper, a number of financial and economic reports are reported as the corpus. First of all, do the text preprocessing, and then based on the N-gram algorithm to generate a set of candidate phrases, and finally use the statistics and the rules to screen for the concept of ontology from candidate phrases.
['Yuefeng Liu', 'Minyong Shi', 'Chunfang Li']
Domain ontology concept extraction method based on text