Capturing the Semantics of Online News Sources for Business Intelligence Applications

In this paper, we present a knowledge based approach to capture rich semantic representations from online news sources for business intelligence (BI) applications that know the representations of interest in advance. Our approach performs this task by generating phrases from these representations and matching these phrases against the news using a set of syntactic and semantic transformations. The representation that best matches a piece of news is selected as its meaning. We present two evaluations showing how our approach performs well on capturing the semantics of online new sources for BI applications.