Please use this identifier to cite or link to this item:
http://hdl.handle.net/10603/483853
Full metadata record
DC Field | Value | Language |
---|---|---|
dc.coverage.spatial | Design of a robust spam detection model using ensemble machine learning methods | |
dc.date.accessioned | 2023-05-17T09:03:17Z | - |
dc.date.available | 2023-05-17T09:03:17Z | - |
dc.identifier.uri | http://hdl.handle.net/10603/483853 | - |
dc.format.extent | xvii,126p. | |
dc.language | English | |
dc.relation | p.115-125 | |
dc.rights | university | |
dc.title | Design of a robust spam detection model using ensemble machine learning methods | |
dc.title.alternative | ||
dc.creator.researcher | Kiruthika Devi K | |
dc.subject.keyword | Social Media | |
dc.subject.keyword | Twitter spam | |
dc.subject.keyword | Cyber security | |
dc.description.note | ||
dc.contributor.guide | Sathish Kumar G A | |
dc.publisher.place | Chennai | |
dc.publisher.university | Anna University | |
dc.publisher.institution | Faculty of Information and Communication Engineering | |
dc.date.registered | ||
dc.date.completed | 2023 | |
dc.date.awarded | 2023 | |
dc.format.dimensions | 21cm | |
dc.format.accompanyingmaterial | None | |
dc.source.university | University | |
dc.type.degree | Ph.D. | |
Appears in Departments: | Faculty of Information and Communication Engineering |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
01_title.pdf | Attached File | 17.45 kB | Adobe PDF | View/Open |
02_prelimpages.pdf | 2.7 MB | Adobe PDF | View/Open | |
03_contents.pdf | 98.25 kB | Adobe PDF | View/Open | |
04_abstracts.pdf | 12.08 kB | Adobe PDF | View/Open | |
05_chapter1.pdf | 617.34 kB | Adobe PDF | View/Open | |
06_chapter2.pdf | 321.3 kB | Adobe PDF | View/Open | |
07_chapter3.pdf | 893.52 kB | Adobe PDF | View/Open | |
08_chapter4.pdf | 673.22 kB | Adobe PDF | View/Open | |
09_chapter5.pdf | 573.67 kB | Adobe PDF | View/Open | |
10_chapter6.pdf | 736.41 kB | Adobe PDF | View/Open | |
11_annexures.pdf | 112.06 kB | Adobe PDF | View/Open | |
80_recommendation.pdf | 118.28 kB | Adobe PDF | View/Open |
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