Аннотация:Online newspaper plays an important role for the development of world.But it consists of several types of labels, titles and links.As online newspapers are collection of variety of newspaper, it is often much more difficult to extract and summarize the news.To improve the accuracy a new algorithm is introduced here based on web extraction and summarization.Firstly, the news from newspapers are extracted which are related to the topic.If different types of news are found about the same topic then it has distinguished.Then a summarization-based algorithm has proposed to summarize the news.Basically, term frequency has used for summarization and evaluate it along with several newspapers' contents.Various forms of words are also compared such as Noun, Adjective, Adverb etc.So that the term frequency can be counted more accurately.It will be very helpful for a user who wants to find out very specific news from the newspapers.
