Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory

Jackson Phiri; Tiejun Zhao

doi:10.1109/ICITIS.2010.5689588

Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory

Jackson Phiri^*
, Tiejun Zhao

^*Corresponding author for this work

School of Computer Science and Technology, Harbin Institute of Technology

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

6 Scopus citations

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.

Original language	English
Title of host publication	Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010
Pages	390-393
Number of pages	4
DOIs	https://doi.org/10.1109/ICITIS.2010.5689588
State	Published - 2010
Externally published	Yes
Event	2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010 - Beijing, China Duration: 17 Dec 2010 → 19 Dec 2010

Publication series

Name	Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010

Conference

Conference	2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010
Country/Territory	China
City	Beijing
Period	17/12/10 → 19/12/10

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 10 Reduced Inequalities

Keywords

Entropy
Identity attributes
Metrics
Multimode authentication
Term weight

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10.1109/ICITIS.2010.5689588

Cite this

Phiri, J., & Zhao, T. (2010). Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory. In Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010 (pp. 390-393). Article 5689588 (Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010). https://doi.org/10.1109/ICITIS.2010.5689588

Phiri, Jackson ; Zhao, Tiejun. / Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory. Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010. 2010. pp. 390-393 (Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010).

@inproceedings{96e222b5de6440f4a243605928023a51,

title = "Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory",

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 = "Entropy, Identity attributes, Metrics, Multimode authentication, Term weight",

author = "Jackson Phiri and Tiejun Zhao",

year = "2010",

doi = "10.1109/ICITIS.2010.5689588",

language = "英语",

isbn = "9781424469406",

series = "Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010",

pages = "390--393",

booktitle = "Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010",

note = "2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010 ; Conference date: 17-12-2010 Through 19-12-2010",

}

Phiri, J & Zhao, T 2010, Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory. in Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010., 5689588, Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010, pp. 390-393, 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010, Beijing, China, 17/12/10. https://doi.org/10.1109/ICITIS.2010.5689588

Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory. / Phiri, Jackson; Zhao, Tiejun.
Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010. 2010. p. 390-393 5689588 (Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution › peer-review

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AB - 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.

KW - Entropy

KW - Identity attributes

KW - Metrics

KW - Multimode authentication

KW - Term weight

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M3 - 会议稿件

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SN - 9781424469406

T3 - Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010

SP - 390

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BT - Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010

T2 - 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010

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ER -

Phiri J, Zhao T. Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory. In Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010. 2010. p. 390-393. 5689588. (Proceedings 2010 IEEE International Conference on Information Theory and Information Security, ICITIS 2010). doi: 10.1109/ICITIS.2010.5689588

Identity attributes quantitative analysis and the development of a metrics model using text mining techniques and information theory

Abstract

Publication series

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UN SDGs

Keywords

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