A Customized Profile-Aware news system for filtering and summarizing

Abstract A significant amount of news material consists of information on the Internet. In Web information, a lot of interest has been devoted to web news tips, filtering, and review, focused at identifying interesting information and analyzing informative user information. We implement our research into the development of the Information Extraction and Summary Process. An integrated part of learning triggers a user interest model and suggests user specific news. An expert system of key words is retained and offers an actual overview to represent the specific matter of web information and the desires of the reader. Not interested and unwanted news content that is unrelated to the news platform is filtered out. Key terms that retrieve the main description of the news Through linguistic sequences, information is retrieved to represent semantic connections between words and Providing refined data, such as a description Versions of the source text and highlights key words in the text that are significant.