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Architecture for Active Conceptual Modeling of Learning.

Authors :
Hutchison, David
Kanade, Takeo
Kittler, Josef
Kleinberg, Jon M.
Mattern, Friedemann
Mitchell, John C.
Naor, Moni
Nierstrasz, Oscar
Pandu Rangan, C.
Steffen, Bernhard
Sudan, Madhu
Terzopoulos, Demetri
Tygar, Doug
Vardi, Moshe Y.
Weikum, Gerhard
Chen, Peter P.
Wong, Leah Y.
Ting, T. C.
Wong, Leah
Source :
Active Conceptual Modeling of Learning; 2008, p7-16, 10p
Publication Year :
2008

Abstract

The concept of Active Conceptual Modeling of Learning (ACM-L) has been explored in order to capture content and context changes that permit a comprehensive learning from the past, understanding the present, and forecasting the future. Such capability has not been fully explored and it is not available with today's static oriented database system. The potential of creating a "database of intention" that can have its own aim to understand the intentions of its users and the changes to their environment. This paper explores an architectural approach for the "database of intention" with predictability power. The proposed architecture is presented, illustrated, and discussed. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISBNs :
9783540775027
Database :
Complementary Index
Journal :
Active Conceptual Modeling of Learning
Publication Type :
Book
Accession number :
33412926
Full Text :
https://doi.org/10.1007/978-3-540-77503-4_2