1. A method for displaying user specific content, said method comprising: determining a size of a random sample of a plurality of links in a browser history; selecting a predetermined number of links from said plurality of links in said browser history for said random sample of said plurality of links; fetching content for each of said plurality of links in said random sample; extracting a plurality of topics comprising a variable number of topics from said content including text from HTML, said extracting of said plurality of topics executed in a background as a low priority process; generating a topic model from said plurality of topics extracted from said content, said topic model to be used to alter a manner in which selected web content is displayed; evaluating content of a newly selected web page against said topic model after generating said topic model to determine a probability score for each of said plurality of topics based on how accurately each of said plurality of topics describes said content of the newly selected web page and by providing every topic in said topic model with said probability score within a certain threshold of all other topics; selecting a subset of said plurality of topics based on said probability score; evaluating said content from said newly selected web page for keywords associated with said subset of topics and which represent significant trends across said subset of tonics; and highlighting said keywords within said newly selected web page based on said topic model in order to display user specific content.