Publication: The Design and Development of Spam Risk Assessment Prototype: In Silico of Danger Theory Variants
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Date
2017
Journal Title
Journal ISSN
Volume Title
Publisher
Science & Information Sai Organization Ltd
Abstract
Now-a-days, data is flowing with various types of information and it is absolutely enormous and moreover, it is in unstructured form. These raw data is meaningless unless it is processed and analyzed to retrieve all the valuable and meaningful information. In this paper, a design and principal functionalities of the system prototype is introduced. A process of information retrieval by applying the text mining with Artificial Immune System (AIS) is proposed to discover the possible level of severity for a Short Messaging Service (SMS) spam. This is expected to be a potential tool in retrieving an implicit danger that a spam might impact to the recipients. Furthermore, the development of this tool can be considered as an emergence of another data mining tool that also exceedingly possible to be embedded with another existing tool.
Description
Keywords
Danger Theory Variants, Text Spam Messages, Severity Assessment, Text Mining, Information Retrieval, Knowledge Discovery