Information retrieval algorithm based on the iterative extraction of key-phrases

In order to ensure that users accurately and quickly obtain what they are interested in from a great amount of knowledge information, an information retrieval algorithm based on the iterative extraction of key-phrases is presented by synthetically considering the head information (title, abstract and keywords) and key body content of a document. By this algorithm, the precision rate of topic extraction reaches 83% with the efficiency being unaffected, and the performance of topic information retrieval is also increased. Experimental results indicate that, by reasonably adjusting the relativity weights of candidate key-phrases on the basis of Term Frequency-In verse Document Frequency and employing the proposed iterative extraction algorithm, the retrieval of topic information can achieve remarkable precision.