Intuitionistic fuzzy recommender systems: An effective tool for medical diagnosis

http://repository.vnu.edu.vn/handle/VNU_123/33082

Title:	Intuitionistic fuzzy recommender systems: An effective tool for medical diagnosis
Authors:	Le, Hoang Son Nguyen, Tho Thong
Keywords:	Accuracy Fuzzy sets Fuzzy sets Medical diagnosis ntuitionistic fuzzy recommender systems
Issue Date:	2015
Publisher:	ELSEVIER SCIENCE BV, PO BOX 211, 1000 AE AMSTERDAM, NETHERLANDS
Citation:	ISIKNOWLEDGE
Abstract:	Medical diagnosis has been being considered as one of the important processes in clinical medicine that determines acquired diseases from some given symptoms. Enhancing the accuracy of diagnosis is the centralized focuses of researchers involving the uses of computerized techniques such as intuitionistic fuzzy sets (IFS) and recommender systems (RS). Based upon the observation that medical data are often imprecise, incomplete and vague so that using the standalone IFS and RS methods may not improve the accuracy of diagnosis, in this paper we consider the integration of IFS and RS into the proposed methodology and present a novel intuitionistic fuzzy recommender systems (IFRS) including: (i) new definitions of single-criterion and multi-criteria IFRS; (ii) new definitions of intuitionistic fuzzy matrix (IFM) and intuitionistic fuzzy composition matrix (IFCM); (iii) proposing intuitionistic fuzzy similarity matrix (IFSM), intuitionistic fuzzy similarity degree (IFSD) and the formulas to predict values on the basis of IFSD; (iv) a novel intuitionistic fuzzy collaborative filtering method so-called IFCF to predict the possible diseases. Experimental results reveal that IFCF obtains better accuracy than the standalone methods of IFS such as De et al., Szmidt and Kacprzyk, Samuel and Balamurugan and RS, e.g. Davis et al. and Hassan and Syed. (C) 2014 Elsevier B.V. All rights reserved.
Description:	KNOWLEDGE-BASED SYSTEMS Volume: 74 Pages: 133-150 Published: JAN 2015 ; TNS05825
URI:	http://www.sciencedirect.com/science/article/pii/S0950705114004043 http://repository.vnu.edu.vn/handle/VNU_123/33082
ISSN:	0950-7051
Appears in Collections:	Bài báo của ĐHQGHN trong Web of Science