Thematic Learning-based Full-text Retrieval Research on British and American Journalistic Reading

Abstract

As for Journalistic Reading Course teaching, it is rather difficult to retrieve instructive and valuable ones from massive online news. In combination with the actual course requirements, the paper endeavors to adopt thematic learning as a means and attach more importance to such three weight indicators as news title, length and timeliness to redesign weight function on the basis of Lucene full-text retrieval algorithm. The comparative experiments prove that the respective addition of length weight, title weight and timeliness weight guarantees the retrieval precision ratio of the top ten improved by 43.6%, 69.2% and 35.9% than before, and by 94.9% after a simultaneous addition of these three weights. It verifies that the search result of the top ten after improvement is more in line with actual teaching requirements in terms of news length and timeliness.