Title :
Fuzzy clustering and categorization of text documents
Author :
Ayeldeen, Heba ; Hassanien, Aboul Ella ; Fahmy, Aly A.
Author_Institution :
Fac. of Comput. & Inf., Cairo Univ., Cairo, Egypt
Abstract :
The fuzzy Euclidean distance clustering algorithm has been well studied and used in information retrieval society for clustering documents. However, the fuzzy logic algorithm poses problems in dealing with large amount of data. In this paper we proposed results for clustering theses documents based on Euclidean distances and cluster-dependent keyword weighting. The proposed approach is based on the Fuzzy Euclidean distance clustering algorithm. The cluster dependent keyword weighting help in partitioning and categorizing the theses documents into more meaningful categories.
Keywords :
data mining; document handling; fuzzy logic; medical computing; ontologies (artificial intelligence); pattern clustering; cluster-dependent keyword weighting; document clustering; fuzzy Euclidean distance clustering algorithm; fuzzy logic algorithm; information retrieval; text document categorization; Biopsy; Catheters; Decision support systems; Ontologies; Pacemakers; Surgery; Ultrasonic imaging; Fuzzy Euclidean distance Algorithm; Lexical similarity; MeSH; Medical Ontology;
Conference_Titel :
Hybrid Intelligent Systems (HIS), 2013 13th International Conference on
Conference_Location :
Gammarth
Print_ISBN :
978-1-4799-2438-7
DOI :
10.1109/HIS.2013.6920493
