Abstract
As business information quickly varies with time, the extraction of knowledge from the related dynamically changing database is vital for business decision making. For an incremental learning optimization on knowledge discovery, a new incremental matrix describes the changes of the system. An optimization incremental algorithm induces interesting knowledge when the object set varies over time. Experimental results validate the feasibility of the incremental learning optimization.
Original language | English |
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Pages (from-to) | 325-344 |
Number of pages | 20 |
Journal | Journal of Global Optimization |
Volume | 51 |
DOIs | |
State | Published - 2011 |