TY - JFULL AU - L. H. Chong and Y. Y. Chen PY - 2009/6/ TI - Text Summarization for Oil and Gas News Article T2 - International Journal of Computer and Information Engineering SP - 1281 EP - 1285 VL - 3 SN - 1307-6892 UR - https://publications.waset.org/pdf/4926 PU - World Academy of Science, Engineering and Technology NX - Open Science Index 29, 2009 N2 - Information is increasing in volumes; companies are overloaded with information that they may lose track in getting the intended information. It is a time consuming task to scan through each of the lengthy document. A shorter version of the document which contains only the gist information is more favourable for most information seekers. Therefore, in this paper, we implement a text summarization system to produce a summary that contains gist information of oil and gas news articles. The summarization is intended to provide important information for oil and gas companies to monitor their competitor-s behaviour in enhancing them in formulating business strategies. The system integrated statistical approach with three underlying concepts: keyword occurrences, title of the news article and location of the sentence. The generated summaries were compared with human generated summaries from an oil and gas company. Precision and recall ratio are used to evaluate the accuracy of the generated summary. Based on the experimental results, the system is able to produce an effective summary with the average recall value of 83% at the compression rate of 25%. ER -