2012/06/27 by Felix Bießmann, Felix Biessmann, Biessmann, Felix +7
Computer Science · Mathematics · Physics and Astronomy · #Complex Network Analysis Techniques #Data Management and Algorithms #FOS: Computer and information sciences #Machine Learning (cs.LG) #Machine Learning (stat.ML) #Social and Information Networks (cs.SI) #Web Data Mining and Analysis #cs.LG #cs.SI #stat.ML
paper · pdf · doi:10.48550/arxiv.1206.6388
Appears in Proceedings of the 29th International Conference on Machine Learning (ICML 2012)
arxiv created 2012/06/27 · openalex publication_date 2012/06/27 · arxiv updated 2012/07/02 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
Much information available on the web is copied, reused or rephrased. The phenomenon that multiple web sources pick up certain information is often called trend. A central problem in the context of web data mining is to detect those web sources that are first to publish information which will give rise to a trend. We present a simple and efficient method for finding trends dominating a pool of web sources and identifying those web sources that publish the information relevant to a trend before others. We validate our approach on real data collected from influential technology news feeds.