| 000 -LEADER |
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| fixed length control field |
03391nam a2200313Ia 4500 |
| 001 - CONTROL NUMBER |
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| control field |
77608 |
| 003 - CONTROL NUMBER IDENTIFIER |
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| control field |
ft6057 |
| 005 - DATE AND TIME OF LATEST TRANSACTION |
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| control field |
20251124095400.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
190426n 000 0 eng d |
| 040 ## - CATALOGING SOURCE |
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| Description conventions |
rda |
| 041 ## - LANGUAGE CODE |
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| Language code of text/sound track or separate title |
engtag |
| 050 ## - LIBRARY OF CONGRESS CALL NUMBER |
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| Classification number |
QA76.9 C36 2017 |
| 055 ## - CLASSIFICATION NUMBERS ASSIGNED IN CANADA |
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| Classification number |
. |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Item number |
2 |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
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| Personal name |
Jerhica Kim T. Canaya and Jolina P. Escolano. |
| 245 #0 - TITLE STATEMENT |
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| Title |
A further enhancement of Paul Graham's Batesian algorithm applied in spam filtering |
| 264 ## - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
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| Place of production, publication, distribution, manufacture |
. |
| Name of producer, publisher, distributor, manufacturer |
. |
| Date of production, publication, distribution, manufacture, or copyright notice |
c2017 |
| 300 ## - PHYSICAL DESCRIPTION |
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| Other physical details |
Undergraduate Thesis: (BSCS major in COmputer Science) -Pamantasan ng Lungsod ng Maynila, 2017. |
| 336 ## - CONTENT TYPE |
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| Content type code |
. |
| Content type term |
text |
| Source |
rdacontent |
| 337 ## - MEDIA TYPE |
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| Materials specified |
0 |
| Media type code |
. |
| Media type term |
unmediated |
| Source |
rdamedia |
| 338 ## - CARRIER TYPE |
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| Materials specified |
0 |
| Carrier type code |
. |
| Carrier type term |
volume |
| Source |
rdacarrier |
| 505 ## - FORMATTED CONTENTS NOTE |
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| Formatted contents note |
ABSTRACT: Nowadays, spammers are just in a corner, sending random and irrelevant mails to our-e-mails, considering that we need to check our received mails for the day. These spam mails may contain malicious words or attachment, links that redirects you to an unwanted website, and some links contain viruses that can harm your computer without even knowing it. These are threats to users, spammers can get information just by simply opening the mail they sent. This research paper presents a variation of token to consider that may use in filtering and number of token to test. This will be beneficial to all who’s using the email to send messages, these may prevent the user in having unnecessary files and viruses attached to the email. We have done manual simulations and computerized simulation to know the possible result of mail stricter. The Paul Graham’s Bayesian algorithm is a machine learning algorithm that trains and classifies a data or a token with different score, we therefore conclude that considering HTML tags and multiple word as token use to determine whether it is from a spam ail or non-spam mail is much effective. In applying this algorithm to spam filtering stricter, we can distinguish whether our received mail is a spam or not. |
| 506 ## - RESTRICTIONS ON ACCESS NOTE |
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| Terms governing access |
5 |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc. |
ABSTRACT: Nowadays, spammers are just in a corner, sending random and irrelevant mails to our-e-mails, considering that we need to check our received mails for the day. These spam mails may contain malicious words or attachment, links that redirects you to an unwanted website, and some links contain viruses that can harm your computer without even knowing it. These are threats to users, spammers can get information just by simply opening the mail they sent. This research paper presents a variation of token to consider that may use in filtering and number of token to test. This will be beneficial to all who's using the email to send messages, these may prevent the user in having unnecessary files and viruses attached to the email. We have done manual simulations and computerized simulation to know the possible result of mail stricter. The Paul Graham's Bayesian algorithm is a machine learning algorithm that trains and classifies a data or a token with different score, we therefore conclude that considering HTML tags and multiple word as token use to determine whether it is from a spam ail or non-spam mail is much effective. In applying this algorithm to spam filtering stricter, we can distinguish whether our received mail is a spam or not. |
| 526 ## - STUDY PROGRAM INFORMATION NOTE |
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| Classification |
Filipiniana |
| 540 ## - TERMS GOVERNING USE AND REPRODUCTION NOTE |
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| Terms governing use and reproduction |
5 |
| 655 ## - INDEX TERM--GENRE/FORM |
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| Genre/form data or focus term |
academic writing |
| 942 ## - ADDED ENTRY ELEMENTS |
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| Institution code [OBSOLETE] |
lcc |
| Item type |
Archival materials |
| Source of classification or shelving scheme |
|