Title :
Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory
Author :
Phiri, Jackson ; Zhao, Tiejun
Author_Institution :
Machine Intell. & Natural Language Process. Group, Harbin Inst. of Technol., Harbin, China
Abstract :
Term weighting has been applied to quantify and rank text data in information retrieval. Shannon´s information theory called entropy is another area that is used to quantify information. In this paper, term weighting and entropy are used to compose an identity attribute metric model. A set of application forms are used to form a sample space of identity attributes and three corpora are used to generate the required statistics used to compose an identity attribute metric model. The composed metric model has application in point based authentication systems, such as banking, immigration and implementing intelligent authentication systems.
Keywords :
data mining; entropy; information retrieval; Shannon information theory; entropy; identity attribute metric model; identity attribute quantitative analysis; information retrieval; point based authentication system; rank text data; term weighting; text mining technique; Authentication; Color; Entropy; Information theory; Measurement; Text mining; Entropy; Identity Attributes; Metrics; Multimode Authentication; Term Weight;
Conference_Titel :
Information Theory and Information Security (ICITIS), 2010 IEEE International Conference on
Conference_Location :
Beijing
Print_ISBN :
978-1-4244-6942-0
DOI :
10.1109/ICITIS.2010.5689588