Multiple leaf nodes based parse trees for News Fetching Systems

With the growth of internet people are shifting from their paper based news system to online news system. These online news websites are very useful for the people who have internet access and they can easily read and search their required news through home/office computer or cell phone without wasting their time. To search a particular news, many searching algorithms and News Fetching Systems (NFS) are available which return the results in less than a second. But how much correct information they are giving from a huge data is still a critical area, where we need some efficient algorithms to give us more optimized results. We propose a Multiple Leaf Nodes based Parse Trees for NFS where all the leaf nodes are commonly used alternative words for a specific word. We evaluate our results for a randomly selected webpage and compare with the simple parse tree system. Analysis shows that our proposed algorithm can enhance the performance of any NFS.