Semantic Hmc For Business Intelligence Using Cross-Referencing

Keeping abreast with current market trends requires the centralization of large amount of information. Due to the increasing number of news available on the web, selecting only valuable information for each consumer is mandatory to reduce the consumer information overload. However, information available on the web can have uncertain and imprecise data, leading to veracity issues. We aim to measure Big Data veracity using cross-referencing of several information sources. In this work we present a new vision to cross-referencing of several huge web information sources using a Semantic Hierarchical Multi-label Classification process called Semantic HMC to extract the knowledge available in those sources.