Recommending medical documents by user profileRecommending medical documents by user profile Περίληψη Δημοσίευσης σε Συνέδριο Conference Paper Abstract 2015-10-282013enThe overwhelmed amount of medical information available online, makes the use of automated recommendation methods essential for identifying relevant information according to user profile needs. This paper presents a method to address the problem of medical document classification into documents for medical professionals (experts) and non-professionals (consumers). Documents are represented by terms extracted from AMTEx, a medical document indexing method, specifically designed for the automatic indexing of documents in large medical collections, such as MEDLINE, and then mapped to the UMLS Semantic Network (SN) categories. Multiple Criteria Decision Analysis (MCDA) tools are applied to calculate the membership of each SN category to the document classification. Several factors such as the classification nature of the problem and the incorporation of common readability formulas are also examined. http://creativecommons.org/licenses/by/4.0/IEEE 13th International Conference on Bioinformatics and Bioengineering Petrakis Evripidis Πετρακης Ευριπιδης Christos Tryfonopoulos Nikos Zevlis Paraskevi Raftopoulou IEEE