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Analyzing email transactions

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dc.contributor.advisor Dr. Sumanta Guha (Chairperson) en_US
dc.contributor.advisor Prof. Phan Minh Dung (Member) en_US
dc.contributor.advisor Dr. Vatcharaporn Esichaikul (Member) en_US
dc.contributor.author Le Cam Loan en_US
dc.date.accessioned 2015-01-12T10:46:21Z
dc.date.available 2015-01-12T10:46:21Z
dc.date.issued 2009 en_US
dc.identifier.other AIT Thesis no.IM-09-08 en_US
dc.identifier.uri http://www.cs.ait.ac.th/xmlui/handle/123456789/631
dc.description 58 p. en_US
dc.description.abstract In a complex Email system with plenty of messages, each user can receive dozens of messages every day. How to recognize which messages should be read first and how to find important or prominent people in the system without knowing the messages’ content. This study focuses on Email transactions that show relationships among entities via messages’ transference in the system to discover important messages and important people from email log. Important messages are messages that contain interesting information or important contents and important people are those who have strong effects on the community via sending and receiving several messages. Two data structures are introduced for this task. The Email transaction multi-digraph is used to represent the email transactions which are encoded in the mail log. Whereas, the messages’ flow is used by the Scoring Model to calculate the scores for email messages based on types of messages (original, forward, or reply). The results of the Scoring Model are used to determine important messages and important people. Some experiments were carried out to verify the methodology and the results showed that this model’s result is acceptable. en_US
dc.description.sponsorship Hau Giang160 – MeKong1000 – Vietnam en_US
dc.language.iso en en_US
dc.publisher Asian Institute of Technology en_US
dc.relation.ispartofseries AIT Publications; en_US
dc.subject Email system en_US
dc.subject Message en_US
dc.subject Email transaction en_US
dc.title Analyzing email transactions en_US
dc.type Thesis en_US


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