Poster Title:

A Novel Clustering-based RSS Aggregator

Authors:

• Xin Li (Peking University)
• Jun Yan (Microsoft Research Asia)
• Zhihong Deng (Peking University)
• Lei Ji (Microsoft Research Asia)
• Weiguo Fan (Virginia Polytechnic Institute and State University)
• Benyu Zhang (Microsoft Research Asia)
• Zheng Chen (Microsoft Research Asia)

Abstract:

In recent years, different commercial Weblog subscribing systems have been proposed to return stories from users' subscribed feeds. In this paper, we propose a novel clustering-based RSS aggregator called as RSS Clusgator System (RCS) for Weblog reading. Note that an RSS feed may have several different topics. A user may only be interested in a subset of these topics. In addition there could be many different stories from multiple RSS feeds, which discuss similar topic from different perspectives. A user may be interested in this topic but do not know how to collect all feeds related to this topic. In contrast to many previous works, we cluster all stories in RSS feeds into hierarchical structure to better serve the readers. Through this way, users can easily find all their interested stories. To make the system current, we propose a flexible time window for incremental clustering. RCS utilizes both link information and content information for efficient clustering. Experiments show the effectiveness of RCS.