Multilayered perceptron feed forward artificial neural network approach for E-mail classification (Record no. 11721)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 01096npc a2200157Ia 4500 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 140613s2013 xx 000 0 und d |
| 060 ## - NATIONAL LIBRARY OF MEDICINE CALL NUMBER | |
| Classification number | 004.692 |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | NONYELUM, OGWUELEKA FRANCISCA |
| 245 ## - TITLE STATEMENT | |
| Title | Multilayered perceptron feed forward artificial neural network approach for E-mail classification |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Date of publication, distribution, etc. | 2013 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | 7-29 |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | E-mail messages are originally designed to be sent and accumulated in repository for periodical use which amounts to the details of an event or a meeting's upcoming agenda for a particular organization. These messages range from static organizational knlowledge to conversations and pose a lot of difficulties to users in terms of prioritizing and processing of the contents of both stored and new incoming messages. This research has established a classification model which classifies the accumulated e-mails in the mail inbox known as dataset into four classes : critical, urgent, important and others. |
| 653 ## - INDEX TERM--UNCONTROLLED | |
| Uncontrolled term | COMPUTER SCIENCE |
| 773 ## - HOST ITEM ENTRY | |
| Other item identifier | P14782 |
| Note | M |
| Host Itemnumber | 33643 |
| Host Biblionumber | 11231 |
| Title | IUP: JOURNAL OF INFORMATION TECHNOLOGY |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Koha item type | Articles |
No items available.