Analyzing Large Collections of E-Mail

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KEIM, Daniel A., Christian PANSE, Jörn SCHNEIDEWIND, Mike SIPS, 2004. Analyzing Large Collections of E-Mail. KE'04. Las Vegas, Nevada, USA, 21. Jun 2004 - 24. Jun 2004. In: Proceedings of the International Conference on Information and Knowledge Engineering. IKE ' 04, June 21 - 24, 2004, Las Vegas, Nevada, USA. KE'04. Las Vegas, Nevada, USA, 21. Jun 2004 - 24. Jun 2004. Las Vegas:CSREA Pr., pp. 275-281

@inproceedings{Keim2004Analy-5613, title={Analyzing Large Collections of E-Mail}, year={2004}, address={Las Vegas}, publisher={CSREA Pr.}, booktitle={Proceedings of the International Conference on Information and Knowledge Engineering. IKE ' 04, June 21 - 24, 2004, Las Vegas, Nevada, USA}, pages={275--281}, author={Keim, Daniel A. and Panse, Christian and Schneidewind, Jörn and Sips, Mike} }

<rdf:RDF xmlns:rdf="http://www.w3.org/1999/02/22-rdf-syntax-ns#" xmlns:bibo="http://purl.org/ontology/bibo/" xmlns:dc="http://purl.org/dc/elements/1.1/" xmlns:dcterms="http://purl.org/dc/terms/" xmlns:xsd="http://www.w3.org/2001/XMLSchema#" > <rdf:Description rdf:about="https://kops.uni-konstanz.de/rdf/resource/123456789/5613"> <dcterms:rights rdf:resource="https://creativecommons.org/licenses/by-nc-nd/2.0/legalcode"/> <dcterms:abstract xml:lang="eng">One of the first applications of the Internet was the electronic mailing (e-mail). Along with the evolution of the Internet, e-mail has evolved into a powerful and popular technology. Messages, electronically documents, pictures and even movies can be send between users of computer systems at different places all over the world within seconds. Electronic mail is a fast, a cheap and a comfortable communication method. But with the exponential increase of the Internet users and the corresponding increasing e-mail traffic, new problems arise. Examples are Spam mails or computer viruses hidden in email attachments. Therefore the analysis of email and email traffic becomes more and more important. In this paper we discuss visualization methods for analyzing large amounts of e-mails to detect interesting patterns or to identify Spam e-mails.</dcterms:abstract> <dc:contributor>Schneidewind, Jörn</dc:contributor> <dc:creator>Schneidewind, Jörn</dc:creator> <dc:contributor>Sips, Mike</dc:contributor> <bibo:uri rdf:resource="http://kops.uni-konstanz.de/handle/123456789/5613"/> <dc:contributor>Panse, Christian</dc:contributor> <dc:date rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:57:12Z</dc:date> <dcterms:available rdf:datatype="http://www.w3.org/2001/XMLSchema#dateTime">2011-03-24T15:57:12Z</dcterms:available> <dc:creator>Panse, Christian</dc:creator> <dcterms:issued>2004</dcterms:issued> <dc:contributor>Keim, Daniel A.</dc:contributor> <dc:rights>deposit-license</dc:rights> <dcterms:bibliographicCitation>First publ. in: Proceedings of the International Conference on Information and Knowledge Engineering. IKE'04, June 21-24, 2004, Las Vegas, Nevada, USA. Las Vegas: CSREA Pr., 2004, pp. 275-281</dcterms:bibliographicCitation> <dc:language>eng</dc:language> <dcterms:title>Analyzing Large Collections of E-Mail</dcterms:title> <dc:creator>Keim, Daniel A.</dc:creator> <dc:creator>Sips, Mike</dc:creator> <dc:format>application/pdf</dc:format> </rdf:Description> </rdf:RDF>

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