voting-based classification for e-mail spam detection
Clicks: 311
ID: 252271
2016
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This
article has not been analysed, so there is no overall score —
reader engagement is measured and shown alongside.
Reader Engagement
Steady Performance
78.0
/100
311 views
220 readers
Trending
AI Quality Assessment
Not analyzed
Readership in this journal
SteadyRanked #2 of 17 articles by views in american journal of orthodontics and dentofacial orthopedics : official publication of the american association of orthodontists, its constituent societies, and the american board of orthodontics
Most read
Least read
Bar heights use a square-root scale.
Mint this article as an NFT
Not yet mintedCreate a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.
5
SUSD
one-off · no wallet required
Abstract
The problem of spam e-mail has gained a tremendous amount of attention. Although entities tend to use e-mail spam filter applications to filter out received spam e-mails, marketing companies still tend to send unsolicited e-mails in bulk and users still receive a reasonable amount of spam e-mail despite those filtering applications. This work proposes a new method for classifying e-mails into spam and non-spam. First, several e-mail content features are extracted and then those features are used for classifying each e-mail individually. The classification results of three different classifiers (i.e. Decision Trees, Random Forests and k-Nearest Neighbor) are combined in various voting schemes (i.e. majority vote, average probability, product of probabilities, minimum probability and maximum probability) for making the final decision. To validate our method, two different spam e-mail collections were used.
| Reference Key |
al-shboul2016journalvoting-based
Use this key to autocite in the manuscript while using
SciMatic Manuscript Manager or Thesis Manager
|
|---|---|
| Authors | ;Bashar Awad Al-Shboul;Heba Hakh;Hossam Faris;Ibrahim Aljarah;Hamad Alsawalqah |
| Journal | american journal of orthodontics and dentofacial orthopedics : official publication of the american association of orthodontists, its constituent societies, and the american board of orthodontics |
| Year | 2016 |
| DOI |
10.5614/itbj.ict.res.appl.2016.10.1.3
|
| URL | |
| Keywords |
Citations
No citations found. To add a citation, contact the admin at info@scimatic.org
Comments
No comments yet. Be the first to comment on this article.