A Hybrid Method for Extracting Key Terms of Text Documents

key terms are important terms in the document, which can give high-level description of contents for the reader. Extracting key terms is a basic step for many problems in natural language processing, such as document classification, clustering documents, text summarization and output the general subject of the document. This article proposed a new method for extracting key terms from text documents. As an important feature of this method, we note the fact that the result of its work is a group of key terms, with terms from each group are semantically related by one of the main subjects of the document. Our proposed method is based on a combination of the following two techniques: a measure of semantic proximity of terms, calculated based on the knowledge base of Wikipedia and an algorithm for detecting communities in networks. One of the advantages of our proposed method is no need for preliminary learning, because the method works with the knowledge base of Wikipedia. Experimental evaluation of the method showed that it extracts key terms with high accuracy and completeness.