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http://oro.open.ac.uk/35095/1/...
Part of book or chapter of book
Data sources: UnpayWall
https://doi.org/10.1007/978-3-...
Part of book or chapter of book . 2010 . Peer-reviewed
Data sources: Crossref
DBLP
Conference object . 2021
Data sources: DBLP
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Email Shape Analysis

Authors: Paul Sroufe; Santi Phithakkitnukoon; Ram Dantu; João W. Cangussu;

Email Shape Analysis

Abstract

Email has become an integral part of everyday life. Without a second thought we receive bills, bank statements, and sales promotions all to our inbox. Each email has hidden features that can be extracted. In this paper, we present a new mechanism to characterize an email without using content or context called Email Shape Analysis. We explore the applications of the email shape by carrying out a case study; botnet detection and two possible applications: spam filtering, and social-context based finger printing. Our in-depth analysis of botnet detection leads to very high accuracy of tracing templates and spam campaigns. However, when it comes to spam filtering we do not propose new method but rather a complementing method to the already high accuracy Bayesian spam filter. We also look at its ability to classify individual senders in personal email inbox’s.

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    This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
    1
    popularity
    This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
    Average
    influence
    This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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    impulse
    This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
Green