The incremental data mining algorithm based on association rules 一種基于關(guān)聯(lián)規(guī)則的增量數(shù)據(jù)挖掘算法
Npsp : an efficient algorithm with incremental data mining for mining sequential patterns 一種高效的序列模式增量挖掘算法
Provide the service on a subscription or pay - per - view basis to generate incremental data revenue 為終端用戶提供訂閱或按次計費服務(wù)來產(chǎn)生數(shù)據(jù)增值業(yè)務(wù)。
The volume of incremental data changes might be low , but the volume of data initially distributed might be high 增量數(shù)據(jù)更改的量可能很小,但初始分發(fā)的數(shù)據(jù)量可能很大。
It applies the initial snapshot to the subscriber and moves and reconciles incremental data changes that occur 它將初始快照應(yīng)用于訂閱服務(wù)器,并移動和協(xié)調(diào)所發(fā)生的增量數(shù)據(jù)更改。
If the table was not empty before the bulk import operation , the cost of revalidating the constraint may exceed the cost of applying check constraints to the incremental data 如果在大容量導(dǎo)入操作之前表不為空,則重新驗證約束的開銷可能超過對增量數(shù)據(jù)應(yīng)用check約束的開銷。
If the table was nonempty before the bulk import operation , the cost of revalidating the constraint may exceed the cost of applying check constraints to the incremental data 如果在大容量導(dǎo)入操作之前表為非空狀態(tài),則重新驗證約束的開銷可能超過將check約束應(yīng)用于增量數(shù)據(jù)的開銷。
It not only could solve the problem of learning on the incremental data sets , but also could considerably reduce the size of traditional decision matrix and avoid the repeated computation in traditional decision matrix algorithm 這不僅解決了動態(tài)數(shù)據(jù)環(huán)境下歸納學(xué)習(xí)問題,而且能降低矩陣空間規(guī)模,避免了傳統(tǒng)決策矩陣算法中的重復(fù)計算。
Therefore , a study of incremental data mining algorithm is urgently needed . incremental data mining only modifies rule sets when database is updated , which takes advantage of previous calculation result and prevents knowledge extraction from the very beginning 把增量算法與數(shù)據(jù)庫的更新結(jié)合在一起,漸增地進(jìn)行知識的更新、修正和加強(qiáng)先前業(yè)已發(fā)現(xiàn)的知識,這樣可以不必重新挖掘全部數(shù)據(jù)。
In order to handle dynamic data set in database of industrial field , several incremental algorithms including nbia and fup are discussed . an improved fast update algorithm with level wise search structure based on fup algorithm is proposed for the incremental data 針對工業(yè)現(xiàn)場數(shù)據(jù)庫動態(tài)更新特點,分析了nbia和fup兩種增量挖掘算法,提出了一種新的在增量數(shù)據(jù)庫基礎(chǔ)上進(jìn)行分層搜索的快速更新算法ifup 。