A Trend Discovery System for Dynamic Web Content Mining
Alberto Méndez-Torreblanca, M. Montes y-Gómez, Aurelio López‐López, Luís Enrique Erro · 2003
The rapid expansion of the web is causing the constant growth of information, leading to several problems such as an increased difficulty of extracting potentially useful knowledge. Web content mining confronts this problem gathering explicit information from different web sites for its access and knowledge discovery. Its current methods focus on analyzing static web sites and cannot deal with constantly changing web sites, such as news sites. In this paper, we propose a method for mining online news sites. This method applies dynamic schemes for exploring these web sites and extracting news reports, and uses domain independent statistical analysis for trend analysis. The overall method is an application of web mining that goes beyond straightforward news analysis, trying to understand current society interests and to measure the social importance of ongoing events.