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Technical University of Crete
Technical University of Crete
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| URI: | http://purl.tuc.gr/dl/dias/6F822D25-9C47-4941-B12E-ABAED6355BE4 | ||
| Year | 2013 | ||
| Type of Item | Conference Paper Abstract | ||
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| Bibliographic Citation | Kleanthi Lakiotaki, Angelos Hliaoutakis, Serafim Koutsos and Euripides G.M. Petrakis.(2013, Nov.). Recommending medical documents by user profile.Presented at IEEE 13th International Conference on Bioinformatics and Bioengineering (BIBE 2013).[Online].Available:http://www.intelligence.tuc.gr/~petrakis/publications/BIBE2013_UserProfile.pdf | ||
| Appears in Collections |
The 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 addressthe 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.
Copyright © DIAS 2013
