A study on an information recommendation system that provides topical information related to user's inquiry for information retrieval
As the Internet has been commonly used in our everyday lives, we have been able to obtain large amount of information from it, whereas we have simultaneously had a problem that it is difficult to find proper information for us from the large amount of information on the Web. Although many information recommendation methods have been proposed in order to solve this problem, most recommendation methods are based on a large amount of user's personal data such as operation log, schedule, etc which means that we have to manage a large amount of personal data in the system in order to provide proper information to users, and it would be expensive to construct such a system. With this background, in this study, against aiming to construct a sophisticated information recommendation system based on large personal data, we propose a handy and not expensive information recommendation method, working beside a normal search engine, which does not depend on user profile data, but on topical news information.
handy information recommendation rss topical information providing ebbinghaus's forgetting curves