@article{(Open Science Index):https://publications.waset.org/pdf/8969,
	  title     = {Identification of Most Frequently Occurring Lexis in Body-enhancement Medicinal Unsolicited Bulk e-mails},
	  author    = {Jatinderkumar R. Saini and  Apurva A. Desai},
	  country	= {},
	  institution	= {},
	  abstract     = {e-mail has become an important means of electronic
communication but the viability of its usage is marred by Unsolicited
Bulk e-mail (UBE) messages. UBE consists of many types
like pornographic, virus infected and 'cry-for-help' messages as well
as fake and fraudulent offers for jobs, winnings and medicines. UBE
poses technical and socio-economic challenges to usage of e-mails.
To meet this challenge and combat this menace, we need to
understand UBE. Towards this end, the current paper presents a
content-based textual analysis of more than 2700 body enhancement
medicinal UBE. Technically, this is an application of Text Parsing
and Tokenization for an un-structured textual document and we
approach it using Bag Of Words (BOW) and Vector Space Document
Model techniques. We have attempted to identify the most
frequently occurring lexis in the UBE documents that advertise
various products for body enhancement. The analysis of such top
100 lexis is also presented. We exhibit the relationship between
occurrence of a word from the identified lexis-set in the given UBE
and the probability that the given UBE will be the one advertising for
fake medicinal product. To the best of our knowledge and survey of
related literature, this is the first formal attempt for identification of
most frequently occurring lexis in such UBE by its textual analysis.
Finally, this is a sincere attempt to bring about alertness against and
mitigate the threat of such luring but fake UBE.},
	    journal   = {International Journal of Computer and Information Engineering},
	  volume    = {6},
	  number    = {4},
	  year      = {2012},
	  pages     = {500 - 504},
	  ee        = {https://publications.waset.org/pdf/8969},
	  url   	= {https://publications.waset.org/vol/64},
	  bibsource = {https://publications.waset.org/},
	  issn  	= {eISSN: 1307-6892},
	  publisher = {World Academy of Science, Engineering and Technology},
	  index 	= {Open Science Index 64, 2012},