Mining linguistic information into an e-retail system

Building more adaptive SW applications is a crucial issue to scale up Information Technology to the Web, where information is organized following different underlying knowledge and/or presentation models. To efficiently manage heterogeneous information sources agents must be able to cooperate, share their knowledge, and agree upon appropriate terminology to be used during interaction. We describe here an e-retail product comparison agent system aiming to supply users with synthesis information on product fitting at best their inquires. We will focus on the Named Entity Recognition and Classification (NERC) component that is very helpful in identifying relevant characteristics in a (multilingual) product description.