Monitoring email transaction logs by text-mining email contents | |
| Author | Chanawut Juntapoln |
| Call Number | AIT RSPR no.CS-11-03 |
| Subject(s) | Electronic mail systems Transaction systems (Computer systems) |
| Note | A research study submitted in partial fulfillment of the requirements for the degree of Master of Engineering in Computer science, School of Engineering and Technology |
| Publisher | Asian Institute of Technology |
| Series Statement | Research studies project report ; no. CS-11-03 |
| Abstract | Email transaction logs can be used to track the unusual events which might appear among message conversations . The problem is that to monitor every single email is taking a lot of effort especially when the size of email transaction log is very large. There fore, it should be a wise option to keep monitoring only the important emails . This research focus es on email message filtering and email content monitoring which are used to create a prototype system of email monitoring in this study . When the filtering percentage and the query terms are obtained, the email message filtering module find s and selects only important messages based on the number of obtained percentage using DFS (Depth First Search algorithm) together with email scoring model. Then, the email content monitoring module analyzes and scores each of email contents comparing to the obtained query terms using VSM (Vector Space Model) together with WordNet database. Finally, the outcome is a list of ranked messages based on their similarity scores. Time to proceed all the system modules rapidly increased when then umber of messages was raised up which means that the filtering module can help to relieve the time - consuming problem especially in a large scale of email transaction logs . In addition, users can manually adjust the most suitable filtering percentage provided by the configuration components . The experiments also show ed that enhancing terms by WordNet helped in rising up the precision value of the system by increasing the opportunity to match among similar terms . Furthermore , increasing the number of messages to be analyze d also ha s significantly raised the recall value of the system |
| Year | 2011 |
| Corresponding Series Added Entry | Asian Institute of Technology. Research studies project report ; no. CS-11-03 |
| Type | Research Study Project Report (RSPR) |
| School | School of Engineering and Technology (SET) |
| Department | Department of Information and Communications Technologies (DICT) |
| Academic Program/FoS | Computer Science (CS) |
| Chairperson(s) | Vatcharaporn Esichaikul; |
| Examination Committee(s) | Guha, Sumanta;Daily, Matthew; |
| Scholarship Donor(s) | Royal Thai Government Fellowship; |
| Degree | Research report (M. Eng.) - Asian Institute of Technology, 2011 |