| dc.contributor.author |
Hamdi, Mohamed Salah |
|
| dc.date.accessioned |
2009-12-30T06:15:35Z |
|
| dc.date.available |
2009-12-30T06:15:35Z |
|
| dc.date.issued |
2006-01-30 |
|
| dc.identifier.citation |
Volume: 21 , Issue: 1 |
en_US |
| dc.identifier.uri |
http://dx.doi.org/10.1109/MIS.2006.14 |
|
| dc.identifier.uri |
http://hdl.handle.net/10576/10580 |
|
| dc.description.abstract |
MASACAD is a multiagent information customization system that adopts the machine-learning paradigm to advise students by mining the Web. In the distributed problem-solving paradigm, systems can distribute among themselves the processes necessary to accomplish a given task. Given the number of problems that distributed processing can address, AI researchers have directed significant effort toward developing specialized problem-solving systems that can interact in their search for a solution. The multiagent-system paradigm embodies this approach. |
en_US |
| dc.language.iso |
en |
en_US |
| dc.subject |
Web mining |
en_US |
| dc.subject |
academic advising |
en_US |
| dc.subject |
expert systems |
en_US |
| dc.subject |
information customization |
en_US |
| dc.subject |
multiagents |
en_US |
| dc.subject |
neural networks |
en_US |
| dc.title |
MASACAD: a multiagent based approach to information customization |
en_US |
| dc.type |
Article |
en_US |