Personalized RSS Search Service Using RSS Characteristics and User Context

Abstract

RSS is a one of the most important techniques in Web 2.0. Although there are a lot of RSS feeds available, finding which information are relevant to user isn't easy. The previous RSS search services have not taken into account RSS feed characteristics and user's contextual information. This seriously limits to offer users with useful information. This paper proposes a new personalized RSS search service using the RSS feed structure and user's context. The proposed method collects the data from RSS service site by categorizing RSS feed structure and then rank RSS channel using RSS tag characteristics and user's context. The system architecture and the search algorithms are described. We design a RSS feed crawler, RSS feed repository and a RSS feed search engine.