PRINCIPLES AND METHODS FOR PERSONALIZING NEWSFEEDS VIA AN ANALYSIS OF INFORMATION NOVELTY AND DYNAMICS

摘要

A system and methodology is provided for filtering temporal streams of information such as news stories by statistical measures of information novelty. Various techniques can be applied to custom tailor news feeds or other types of information based on information that a user has already reviewed. Methods for analyzing information novelty are provided along with a system that personalizes and filters information for users by identifying the novelty of stories in the context of stories they have already reviewed. The system employs novelty-analysis algorithms that represent articles as a bag of words and named entities. The algorithms analyze inter- and infra- document dynamics by considering how information evolves over time from article to article, as well as within individual articles.