NDLI: Personalized Spam Filtering with Semi-supervised Classifier Ensemble

Content Provider	IEEE Xplore Digital Library
Author	Victor Cheng Li, C.H.
Copyright Year	2006
Description	Author affiliation: Dept. of Comput. Sci., Hong Kong Baptist Univ. (Victor Cheng; Li, C.H.)
Abstract	The proliferation of unsolicited emails, also known as spam, poses significant burden to email users worldwide. Recent researches on spam filtering have shown that high accuracies can be obtained if labeled emails examples are available from the particular user of the spam filter. However, the time consuming process of providing personalized labeled training examples is often inconvenient or impossible due to privacy issues. In this paper, a semi-supervised personalized spam filter based on classifier ensemble is proposed that classifies user's emails accurately by learning on both generic labeled emails and personalized unlabeled emails. The proposed multi-stage classification process begins learning a SVM model from labeled generic data. Unlabeled user's emails are then fed to this SVM to generate personalized labeled data for constructing personalized naive Bayes classifiers. Furthermore, some personalized labeled examples are generated by exploiting rare word distributions and then fed into a semi-supervised classifier. The multi-stage results are integrated with SVMs learned from generic labeled emails to produce the final classification results. Experimental results show that the proposed approaches can significantly increases the classification accuracy in spam filtering
Sponsorship	IEEE Comput. Soc. WIC ACM
Starting Page	195
Ending Page	201
File Size	299115
Page Count	7
File Format	PDF
ISBN	0769527477
DOI	10.1109/WI.2006.132
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2006-12-18
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Support vector machines Computer science Privacy Unsolicited electronic mail Support vector machine classification Machine learning Information filters Information filtering Internet Testing
Content Type	Text
Resource Type	Article

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

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