  Decision makers need economical information to drive their decisions. The
Company Actualis SARL is specialized in the production and distribution of a
press review about French regional economic actors. This economic review
represents for a client a prospecting tool on partners and competitors. To
reduce the overload of useless information, the company is moving towards a
customized review for each customer. Three issues appear to achieve this goal.
First, how to identify the elements in the text in order to extract objects
that match with the recommendation's criteria presented? Second, How to define
the structure of these objects, relationships and articles in order to provide
a source of knowledge usable by the extraction process to produce new knowledge
from articles? The latter issue is the feedback on customer experience to
identify the quality of distributed information in real-time and to improve the
relevance of the recommendations. This paper presents a new type of
recommendation based on the semantic description of both articles and user
profile.
