Authors:
David Werner
;
Christophe Cruz
and
Christophe Nicolle
Affiliation:
UMR CNRS 5158, France
Keyword(s):
Recommender Systems, Multi-ontologies, Information Extraction, OBIE, Ontology-based, Knowledge-based.
Related
Ontology
Subjects/Areas/Topics:
Biomedical Engineering
;
Data Engineering
;
Enterprise Information Systems
;
Health Information Systems
;
Information Systems Analysis and Specification
;
Knowledge Management
;
Ontologies and the Semantic Web
;
Ontology and the Semantic Web
;
Society, e-Business and e-Government
;
Web Information Systems and Technologies
;
Web Interfaces and Applications
Abstract:
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 recommen
dation based on the semantic description of both articles and user profile.
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